ESRA 2015 Sessions

Advanced statistical modeling (HT-101)

Convenor Dr Jarl Kampen (Research Methodology Group, Wageningen UR, The Netherlands)


Analyses of social change with cross-sectional and longitudinal data 1 (L-101)

Convenor Ms Malgorzata Mikucka (Universite catholique de Louvain)
Coordinator 1Mr Francesco Sarracino (STATEC, Luxembourg)

The availability of repeated cross-sectional surveys and of panel data allows analyzing social change over time. This kind of analyses became popular after the recent studies on the relationship between economic growth and the trends of subjective well-being. Since then, this approach has been applied in various domains. Currently, researchers are increasingly interested in combining longitudinal and cross-sectional approaches to study social change. However, this field of research is still in its infancy and consequences of various methodological choices are still not well understood.

This session invites papers discussing the conceptual and methodological problems of analyzing social change over time with data such as macro-level time series, cross-sectional, and longitudinal surveys. In particular we welcome substantive research which investigates social change over time, presents novel methodological approaches, as well as postulates “good practices” in analyzing such data. The topics include, but are not restricted to:

1. Research which investigates short- and long-term trends over time, as well as discusses methods of estimating trends and their consequences;
2. Analyses of relationships between changes occurring in various domains of social life, performed both within time-series and comparative frameworks;
3. Papers that distinguish between the effects of cross-sectional differences and the effects of overtime changes of the same factors;
4. Studies analyzing social change with comparative panel data.


Assessing the Quality of Survey Data 1 (O-201)

Convenor Professor Joerg Blasius (University of Bonn)

This session will provide a series of original investigations on data quality in both national and international contexts. The starting premise is that all survey data contain a mixture of substantive and methodologically-induced variation. Most current work focuses primarily on random measurement error, which is usually treated as normally distributed. However, there are a large number of different kinds of systematic measurement errors, or more precisely, there are many different sources of methodologically-induced variation and all of them may have a strong influence on the “substantive” solutions. To the sources of methodologically-induced variation belong response sets and response styles, misunderstandings of questions, translation and coding errors, uneven standards between the research institutes involved in the data collection (especially in cross-national research), item- and unit non-response, as well as faked interviews. We will consider data as of high quality in case the methodologically-induced variation is low, i.e. the differences in responses can be interpreted based on theoretical assumptions in the given area of research. The aim of the session is to discuss different sources of methodologically-induced variation in survey research, how to detect them and the effects they have on the substantive findings.


Assuring Measurement Quality in the Social Sciences – new standards for quality documentation 1 (O-106)

Convenor Professor Beatrice Rammstedt (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 1Dr Natalja Menold (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 2Dr Constanze Beierlein (GESIS - Leibniz Institute for the Social Sciences)

Conclusions drawn from survey data can only be reliable if the survey instruments (e.g. survey questions and questionnaires) are of sufficient quality. Based on the Total Survey Error approach accessing and documentation of measurement quality in surveys will be addressed. The aim of the session is to evaluate existing standards and current survey practices with respect to the measurement error in surveys and to discuss advantages and limitations as well future developments. Researchers are invited to submit papers dealing with standards and practices in assessment and documentation of measurement quality in surveys, such as assuring the validity of a measure as well diminishing non-systematic, systematic, and processing errors.


Basic Human Values 1 (N-132)

Convenor Professor Eldad Davidov (University of Zurich)
Coordinator 1Dr Jan Cieciuch (University of Zurich and Cardinal Stefan Wyszyński University in Warsaw)
Coordinator 2Dr Constanze Beierlein (GESIS)

The 4th session organizer is Professor Peter Schmidt, peter.schmidt@sowi.uni-giessen.de, University of Giessen

Values have held an important position in the social sciences since their inception. Max Weber treated values as a central component in his analysis of capitalist society, linking the development of capitalism to the values of the Protestant Ethic. Values have played an important role not only in sociology, but in social psychology, anthropology, political science and related disciplines as well. They have been used to explain the motivational bases of attitudes and behavior and to characterize differences between both individuals and societies.

In 1992, Schwartz introduced a theory of ten basic human values, building on common elements in earlier approaches. The designers of the European Social Survey (ESS) chose this theory as the basis for developing a human values scale to include in the core of the survey. Recently, this theory has been extended to include 19 values (Schwartz et al., 2012) and a new scale, the PVQ-RR, has been developed to measure them.

In this session continuing work on basic human values as postulated by Schwartz will be presented. Presentations which discuss (1) The measurement of human values; (2) Values as predictors of attitudes, opinions or behaviour; (3) Value change; and related topics are welcome. Both substantive and methodological papers using cross-sectional, cross-cultural or longitudinal datasets are welcome.


Comparing the individual name, address and household samples in comparative surveys (HT-102)

Convenor Dr Piotr Jabkowski (Institute of Sociology, University of Poznan, Poland)
Coordinator 1Professor Ryszard Cichocki (Quality of LIfe Research Centre, University of Poznan, Poland)

Existing literature on survey methodology is not rich in studies of the relationship between the type of sample-frames and the patterns of their fieldwork execution. Most studies focus on the impact of the within-household selection of respondent (characteristic of the address and household samples) on the imperfect coverage of the individuals comprising the population; much less attention has been devoted to the problem of what effects the different sample-frames have on the response-rates and the post-survey structure of the set of respondents and non-respondents.

On the one hand, given the necessity of multi-stage selection of respondents in address and household samples, one would expect lower response and cooperation rates than in the individual-name samples. On the other hand, due to the fact that in the address and household samples there are limits of the control that researchers actually have over the respondent selection, the interviewers may be inclined to select respondent with a higher readiness to cooperate. In other words, if there were to be systematic irregularities committed in the selection of individuals within address and household samples, the contact rates should be higher and refusal rates lower than in individual samples.

The present session would focus on theoretical issues and practical challenges connected with:
- the process of intra-unit selection of respondents;
- within-unit coverage errors;
- statistical consequences of random selection of individuals within address / household samples;
- data sources for individual and address-based / household samples;
- fieldwork based on address and individual-based / household samples;
- response rates in address and individual-based / household samples;
- cooperation and refusal rates in address / household and individual-based samples.


Design of Response Scales in (Mobile) Web Surveys (HT-104)

Convenor Mrs Franziska Gebhard (University of Mannheim)
Coordinator 1Professor Vera Toepoel (Utrecht University)
Coordinator 2Professor

This session focuses on the latest methodology research on ratings scales for desktop and mobile surveys. The two main topics are the implementation of graphical rating scales in online surveys, and the design of answer formats for online, mixed-device, or mobile surveys.

Web surveys offer a wide range of possibilities to design answer scales that are unique to this mode of data collection. Graphical elements like for example slider scales are sometimes used as replacement for rather conventional HTML elements (e.g., radio buttons or checkboxes). Yet the question remains if the quality of these data is the same, there might also be a difference between measurement effects and respondent preferences.

Furthermore, the use of mobile phones or tablets increases. Thus, researchers face new challenges when designing response scales also for small screen devices or devices that are operated by touch screen. Liquid or responsive questionnaire designs (e.g., grid questions on desktop computers versus one item per page on smartphones) as well as new HTML5 input types try to tackle these problems. However, this actually leads to different question contexts, which could affect question understanding and data quality. For example, rating scales optimized for touch screen devices (e.g., HTML5 slider scales or date/time picker) could lead to different ratings on desktop computers.

We encourage submitting papers with a focus on
– the impact of graphical rating scales on data quality
– the implementation of response scales in mixed-device or mobile Web surveys
– new HTML5 input types (e.g., date/time picker, range, or autocomplete)


Experimental designs in online survey research 1 (L-102)

Convenor Mr Henning Silber (Göttingen University)
Coordinator 1Mr Jan Karem Hoehne (Göttingen University)
Coordinator 2Professor Dagmar Krebs (Giessen University)

Experimental studies have become increasingly popular in survey research and are carried out in various disciplines such as sociology, political science, linguistics, economics and psychology. In survey research experimental designs are useful tools to get a better understanding of cognitive processes in order to give better practice advice for improving study and questionnaire design. In particular, the technological advances have made it significantly easier to use experimental designs in online field experiments as well as in computerized laboratory experiments.

This session invites presentations on empirical studies and theoretical discussions of experimental designs in online survey research.

- Empirical online research can include studies on response behavior and social desirability bias, as well as experiments on response rates and question design effects. Furthermore, we especially encourage presentations with replicated experimental results and welcome replications in different social contexts such as different cultural, educational and ethnic groups.
- Additionally, we invite presentations that discuss the value of experiments from a theoretical perspective. Theoretical presentations could contrast the merits and the limits of different forms of experimental study designs or provide a future outlook on the prospects of online experiments in survey research.

Presentations could cover the following research areas:

- Theory of experimental study designs
- Replication of experimental results
- Comparisons between different experimental designs (e. g., laboratory and field experiment)
- Split-ballot experiments (e. g., context effects, question order, response order, acquiescence, visual design effects, verbal effects)
- Choice experiments
- Laboratory experiments on response behavior (e. g., using eye tracking)
- Experiments with incentives
- Vignette studies
- Future prospects of experimental designs


Interviewers’ Deviations in Surveys 1 (O-202)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Professor Peter Winker (University of Giessen)

Interviewers’ behavior might have an impact on survey data. The session deals with deviations from the instructions when contacting and interviewing respondents. These deviations might be caused by different factors such as task difficulty, interviewers’ ability, experience and motivation, but also by the quality of questionnaires and instructions. Deviations might result in bias, but could also foster data quality, e.g. if interviewers try to help the respondents in providing a (correct) answer. The session aims to discuss both, deliberate (e.g. falsifications; providing explanation) and non-deliberate deviations (e.g. interviewers’ mistakes).
Researchers are invited to submit papers dealing with all kinds of interviewers’ deviations in the survey process which might result in non-observation or measurement errors but also positively influence survey outcomes. Of interest are theoretical approaches and empirical studies on detection and prevention, on explanatory factors and consequences of interviewers’ deviations. Thus, interviewers’ motivation to deviate from prescribed standards or to produce high quality survey data as well as interviewers’ cognitive skills and competencies could be of interest.


Recent advances in business survey methodology (O-206)

Convenor Professor Hans Kiesl (Regensburg University of Applied Sciences)

Business surveys differ from household surveys in several respects and pose problems like an ambiguous definition of the survey units (firm or establishment), outdated frames, highly skewed distributions of interest, large differences in weights due to the usual pps design, and stratum jumpers (i.e. business units changing size class between the time of drawing the sample and actually surveying the sampled units).

This session aims to bring together researchers from different countries who are coping with methodological problems of business surveys. A special focus will lie on papers dealing with recent developments in job vacancy surveys, which are conducted in every member state of the European Union (and several other countries outside the EU).


Social indicators as predictors of subjective well-being (N-131)

Convenor Mr Nicholas Otis (McGill University)

A growing body of empirical evidence suggests that numerous subjective and objective factors are significantly associated with individual well-being. However, the interplay and causal linkages between these factors are frequently contested. Questions tapping well-being often vary between surveys, potentially impacting research outcomes. In this session, presenters are invited to share research examining the relationships between a diverse range of measures of well-being and its determinants. We encourage submissions from a wide variety of disciplinary, theoretical, and methodological backgrounds.


Surveying immigrants and minorities from a comparative cross-country perspective 1 (L-103)

Convenor Professor Hans-jürgen Andreß (Universität zu Köln)
Coordinator 1Dr Rossalina Latcheva (European Union Agency for Fundamental Rights)
Coordinator 2Ms Ursula Till-tentschert (European Union Agency for Fundamental Rights)

Despite the ongoing demand for data on immigrants and ethnic minorities and the increasing availability of immigrant statistics, a considerable lack of comparable data on immigrants and ethnic minorities still persists. The reasons for this are manifold, e.g. diverging definitions of the target groups (by ethnicity, country of birth and country of birth of parents, nationality, and citizenship) and difficulties to properly cover the target population with traditional data collection methods.

One of the main challenges faced by survey researchers are incomplete or the lack of sampling frames. A cross-country and/or cross-cultural survey design introduces additional complexity in surveying immigrants and ethnic minorities. The heterogeneity in regard to applied methodologies (sampling, data collection modes, questionnaire design, translation and weighting) as well as with regard to legal status, language proficiency, and cultural norms of the target populations has an effect on the coherence of results between different groups of origin and between national contexts. Moreover, standard questionnaire classifications, such as ISCED for educational attainment, cannot easily be applied to immigrants and therefore calls for new concepts to be developed and applied.
This session welcomes contributions that focus on these challenges and that offer solutions for some of the difficulties discussed. It welcomes theoretical contributions as well as survey applications in a cross-country or cross-cultural setting, with a special focus on immigrants, their descendants and ethnic minorities. We particularly encourage submissions which apply a comparative perspective to the following dimensions in survey research:
• Identification and definition of target groups
• Availability and accessibility of different sampling frames and their impact
• Application of different sampling strategies within one survey
• Approaches to reaching target populations
• Differences in field work organisation, training of interviewers
• Modes of interviewing and survey design
• Questionnaire design and translation
• Application of standard classifications
• Weighting


Surveying precarious topics (O-101)

Convenor Mr Simon Henke (GESIS - Leiniz Institute for the Social Sciences)

Sometimes social surveys are interested in very precarious topics. This can be unrecorded crime, very personal topics (e.g. sex) or even opinions, attitudes or behavior which might be stigmatized within the host society. This session should talk about how it is possible to get the right answer or if not what methods are possible to evaluate the credibility of the given answers.

How well do randomized response techniques (RRT) work in social surveys or which more recent techniques are used (e.g. Unmatched Count Technique, Non-randomized response approach)? Another way to get the correct answer within personal interviews could be to force the interviewer to evaluate the credibility of the given answers. This credibility diagnostic is typically done by the police or within court actions, but this might also be a technique for social surveys on precarious topics. The session is especially interested in experience with these techniques, but also in all practical implementation to get information about precarious topics.


Using Paradata to Improve Survey Data Quality 1 (HT-103)

Convenor Professor Volker Stocké (University of Kassel, Germany)
Coordinator 1Professor Jochen Mayerl (TU Kaiserslautern, Germany)
Coordinator 2Dr Oliver Lipps (Swiss Centre of Expertise in the Social Sciences (FORS), Lausanne, Switzerland)

“Paradata” are measures generated as a by-product of the survey data collection process. Prominent examples of paradata are data available from the sampling frame, call-record data in CATI surveys, keystroke information from CAI, timestamp files, observations of interviewer behavior or respondents’ response latencies (see Kreuter 2013 for an overview). These data can potentially be used to enrich questionnaire responses or to provide additional information about the survey (non-)participation process. In many cases paradata are available at no (or little) additional cost, but the theoretical basis for using paradata as indicator for survey data quality is very underdeveloped. Some examples about the use of paradata are:

Paradata in fieldwork monitoring and nonresponse research: Paradata are often used in the survey management context. With control charts survey practitioners can monitor fieldwork progress and interviewer performance. They are also indispensable in responsive designs as real-time information about fieldwork and survey outcomes which affect costs and errors. However, their role as indicator for interviewer or fieldwork effects, as well as predictors for nonresponse is unclear.

Paradata to understand respondent behavior: Paradata might aid assessing of the quality of survey responses, e.g. by means of response latencies or back-tracking. Research has used paradata to identify uncertainty in the answers given by respondents, e.g., if respondents frequently alter their answers. In this new strand of research, however, indicators might still be confounded and tap into multiple dimensions of the response process (e.g., response latencies may be an indicator for retrieval problems and/or satisficing).


Web surveys: challenges and strategies (HT-105)

Convenor Dr Maria Clelia Romano (ISTAT)
Coordinator 1Dr Francesca Gallo (ISTAT)

Over the past decade the use of Internet has brought a profound effect on the survey methodology and the CAWI technique has received great attention from social researchers.
Social surveys can greatly benefit of the web techniques for two main reasons: on the one hand, the relative low cost of conducting web surveys makes them very competitive and well suited to the current budget constraints; on the other hand, they give a better chance to reach subgroups of population hardly accessible with other techniques.
Furthermore, the combined use of different survey techniques allows to improve the target population coverage and to overcome the drawbacks related to each single technique.
Nevertheless, the CAWI technique requires a great effort in order to design or redesign the entire survey system: the questionnaire, the interaction mode with the respondents, the reminder system and so on.
Although recent literature has provided interesting contributions, there are still gaps in our knowledge on how to deal with official government surveys, which are often much complex and involve a great deal of editing.
The researchers have to face old and new challenges, in a new context, which is strongly characterized by the spread of new technologies. Some of these challenges include the optimal design for questions that require complex coding (e.g. economic activity or occupation), the development of effective instructions to explain complex statistical concepts to respondents or the navigation improvement for complex household questionnaires.
Moreover, in the case of mixed mode, which techniques to combine in order to get the best from each? In which sequence?
The proposed session aims at sharing and discussing the ongoing experiences on web surveys on individuals and on mixed mode techniques including web. New approaches and best practices to improve data quality of the NSIs web surveys are extremely welcome.


Analyses of social change with cross-sectional and longitudinal data 2 (L-101)

Convenor Ms Malgorzata Mikucka (Universite catholique de Louvain)
Coordinator 1Mr Francesco Sarracino (STATEC, Luxembourg)

The availability of repeated cross-sectional surveys and of panel data allows analyzing social change over time. This kind of analyses became popular after the recent studies on the relationship between economic growth and the trends of subjective well-being. Since then, this approach has been applied in various domains. Currently, researchers are increasingly interested in combining longitudinal and cross-sectional approaches to study social change. However, this field of research is still in its infancy and consequences of various methodological choices are still not well understood.

This session invites papers discussing the conceptual and methodological problems of analyzing social change over time with data such as macro-level time series, cross-sectional, and longitudinal surveys. In particular we welcome substantive research which investigates social change over time, presents novel methodological approaches, as well as postulates “good practices” in analyzing such data. The topics include, but are not restricted to:

1. Research which investigates short- and long-term trends over time, as well as discusses methods of estimating trends and their consequences;
2. Analyses of relationships between changes occurring in various domains of social life, performed both within time-series and comparative frameworks;
3. Papers that distinguish between the effects of cross-sectional differences and the effects of overtime changes of the same factors;
4. Studies analyzing social change with comparative panel data.


Assessing the Quality of Survey Data 2 (O-201)

Convenor Professor Joerg Blasius (University of Bonn)

This session will provide a series of original investigations on data quality in both national and international contexts. The starting premise is that all survey data contain a mixture of substantive and methodologically-induced variation. Most current work focuses primarily on random measurement error, which is usually treated as normally distributed. However, there are a large number of different kinds of systematic measurement errors, or more precisely, there are many different sources of methodologically-induced variation and all of them may have a strong influence on the “substantive” solutions. To the sources of methodologically-induced variation belong response sets and response styles, misunderstandings of questions, translation and coding errors, uneven standards between the research institutes involved in the data collection (especially in cross-national research), item- and unit non-response, as well as faked interviews. We will consider data as of high quality in case the methodologically-induced variation is low, i.e. the differences in responses can be interpreted based on theoretical assumptions in the given area of research. The aim of the session is to discuss different sources of methodologically-induced variation in survey research, how to detect them and the effects they have on the substantive findings.


Assuring Measurement Quality in the Social Sciences – new standards for quality documentation 2 (L-103)

Convenor Professor Beatrice Rammstedt (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 1Dr Natalja Menold (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 2Dr Constanze Beierlein (GESIS - Leibniz Institute for the Social Sciences)

Conclusions drawn from survey data can only be reliable if the survey instruments (e.g. survey questions and questionnaires) are of sufficient quality. Based on the Total Survey Error approach accessing and documentation of measurement quality in surveys will be addressed. The aim of the session is to evaluate existing standards and current survey practices with respect to the measurement error in surveys and to discuss advantages and limitations as well future developments. Researchers are invited to submit papers dealing with standards and practices in assessment and documentation of measurement quality in surveys, such as assuring the validity of a measure as well diminishing non-systematic, systematic, and processing errors.


Basic Human Values 2 (N-132)

Convenor Professor Eldad Davidov (University of Zurich)
Coordinator 1Dr Jan Cieciuch (University of Zurich and Cardinal Stefan Wyszyński University in Warsaw)
Coordinator 2Dr Constanze Beierlein (GESIS)

The 4th session organizer is Professor Peter Schmidt, peter.schmidt@sowi.uni-giessen.de, University of Giessen

Values have held an important position in the social sciences since their inception. Max Weber treated values as a central component in his analysis of capitalist society, linking the development of capitalism to the values of the Protestant Ethic. Values have played an important role not only in sociology, but in social psychology, anthropology, political science and related disciplines as well. They have been used to explain the motivational bases of attitudes and behavior and to characterize differences between both individuals and societies.

In 1992, Schwartz introduced a theory of ten basic human values, building on common elements in earlier approaches. The designers of the European Social Survey (ESS) chose this theory as the basis for developing a human values scale to include in the core of the survey. Recently, this theory has been extended to include 19 values (Schwartz et al., 2012) and a new scale, the PVQ-RR, has been developed to measure them.

In this session continuing work on basic human values as postulated by Schwartz will be presented. Presentations which discuss (1) The measurement of human values; (2) Values as predictors of attitudes, opinions or behaviour; (3) Value change; and related topics are welcome. Both substantive and methodological papers using cross-sectional, cross-cultural or longitudinal datasets are welcome.


Conversations across the fence: Lessons for business survey methods drawn from social surveys, and vice-versa (O-206)

Convenor Mr Alfred Tuttle (United States Census Bureau)

Although typically treated separately in the literature and in practice, surveys of businesses and other organizations have much in common with social surveys of persons and households, namely that they are all completed by human beings. Effective survey requests, collection methods, and communications processes must be designed around the ways people think, interact with survey instruments, and communicate, whether they are being asked about the characteristics of their households or those of their employer.

While business surveys must contend with the additional dimensions of job specialization, information management systems, processes for coordinating work, and organizational goals and priorities, the basic cognitive processes involved in completing either type of survey (comprehension, retrieval, judgment, reporting) remain the same. Likewise, decisions about complying with survey requests are activated by social norms and psychological processes, such as altruism, cost-benefit analyses, social exchange theory, etc.

Thus, in large part, researchers have adapted and modified well-developed social survey methods for application in business surveys. However, with the advent of Web surveys, social surveys, traditionally conducted by interviewers, have been migrating to self-administration, long the primary data collection mode for business surveys. The evolution of the digital world has led to convergences in the design of, for example, Web pages and other electronic interfaces. Common practices in user-centered design shape norms for online interactions and the expectations of users, which become pertinent for both social and business surveys alike.

The purpose of this session is to engender dialogue among survey methodologists from both realms, considering both the application of lessons learned from social surveys to business surveys, and adaptations for business survey methods beyond those required for social surveys. The focus will be on questionnaire evaluation, design, testing and implementation of collection instruments, communication strategies, and other data collection procedures.


Direction of Response Scales (HT-104)

Convenor Dr Florian Keusch (University of Michigan)
Coordinator 1Professor Ting Yan (University of Michigan)

The measurement of many constructs in social and marketing research, such as attitudes, opinions, behaviors, personality traits, and personal states, heavily relies on the use of response scales. Survey literature has demonstrated that many design features of response scales (e.g., number of scale points, numeric and verbal labels, spacing of response options, alignment) affect how survey respondents process the scale and use these features to construct their responses. A response scale could run from the positive to the negative pole (e.g., “strongly agree” to “strongly disagree”) or the highest to the lowest point (e.g., “all of the time” to “never”). The same scale could also run from the negative to the positive pole (e.g., “strongly disagree” to “strongly agree”) or the lowest to the highest point (e.g., “never” to “all of the time”). An important question is then whether or not the direction of a response scale affects survey answers, holding constant the other features of the scale.
This session invites presentations that investigate the influence of scale direction on survey responses. We particularly invite presentations that analyze the influence of scale direction (1) under different modes of data collection, especially emerging modes, such as mobile Web and SMS/texting, (2) considering moderating effects of scale- and question-level characteristics, such as number of scale points, scale alignment, and question content, and (3) in a cross-cultural context.


Experimental designs in online survey research 2 (L-102)

Convenor Mr Henning Silber (Göttingen University)
Coordinator 1Mr Jan Karem Hoehne (Göttingen University)
Coordinator 2Professor Dagmar Krebs (Giessen University)

Experimental studies have become increasingly popular in survey research and are carried out in various disciplines such as sociology, political science, linguistics, economics and psychology. In survey research experimental designs are useful tools to get a better understanding of cognitive processes in order to give better practice advice for improving study and questionnaire design. In particular, the technological advances have made it significantly easier to use experimental designs in online field experiments as well as in computerized laboratory experiments.

This session invites presentations on empirical studies and theoretical discussions of experimental designs in online survey research.

- Empirical online research can include studies on response behavior and social desirability bias, as well as experiments on response rates and question design effects. Furthermore, we especially encourage presentations with replicated experimental results and welcome replications in different social contexts such as different cultural, educational and ethnic groups.
- Additionally, we invite presentations that discuss the value of experiments from a theoretical perspective. Theoretical presentations could contrast the merits and the limits of different forms of experimental study designs or provide a future outlook on the prospects of online experiments in survey research.

Presentations could cover the following research areas:

- Theory of experimental study designs
- Replication of experimental results
- Comparisons between different experimental designs (e. g., laboratory and field experiment)
- Split-ballot experiments (e. g., context effects, question order, response order, acquiescence, visual design effects, verbal effects)
- Choice experiments
- Laboratory experiments on response behavior (e. g., using eye tracking)
- Experiments with incentives
- Vignette studies
- Future prospects of experimental designs


Interaction effects and group comparisons in nonlinear models (HT-101)

Convenor Mr Heinz Leitgöb (University of Linz, Austria)
Coordinator 1Professor Stefanie Eifler (University of Eichstätt-Ingolstadt, Germany)

In contrast to the linear model, the identification of interaction effects and differences in effects between groups in nonlinear models (e.g. logit, probit, Poisson, negative binomial, PH, AFT) is complicated by link functions deviating from identity form and constraints on the variance of random components. As a consequence, many traditional analytical strategies elaborated within the linear modeling approach proved as not appropriate for the identification of the aforementioned effects in nonlinear models. Thus far, this fact has not received all the attention it deserves.

For this reason we warmly welcome presentations dealing with
(i) the identification of interaction effects in all kinds of nonlinear models,
(ii) the separation of model inherent and product term induced interaction effects,
(iii) the relevance of model inherent interaction from a theoretical point of view,
(iv) the identification of differences in effects between groups in all kinds of nonlinear models, and
(v) the isolation of scaling effects in coefficients between groups.

Further, we highly appreciate presentations containing respective empirical applications.


Interviewers’ Deviations in Surveys 2 (O-202)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Professor Peter Winker (University of Giessen)

Interviewers’ behavior might have an impact on survey data. The session deals with deviations from the instructions when contacting and interviewing respondents. These deviations might be caused by different factors such as task difficulty, interviewers’ ability, experience and motivation, but also by the quality of questionnaires and instructions. Deviations might result in bias, but could also foster data quality, e.g. if interviewers try to help the respondents in providing a (correct) answer. The session aims to discuss both, deliberate (e.g. falsifications; providing explanation) and non-deliberate deviations (e.g. interviewers’ mistakes).
Researchers are invited to submit papers dealing with all kinds of interviewers’ deviations in the survey process which might result in non-observation or measurement errors but also positively influence survey outcomes. Of interest are theoretical approaches and empirical studies on detection and prevention, on explanatory factors and consequences of interviewers’ deviations. Thus, interviewers’ motivation to deviate from prescribed standards or to produce high quality survey data as well as interviewers’ cognitive skills and competencies could be of interest.


Survey data in composite indexes of well-being and socio-economic development 1 (N-131)

Convenor Professor Krzysztof Zagorski (Kozminski University)

There is a growing interest in composite indexes of well-being and socio-economic development, such as OECD “Better Life Index”, Kingdom of Buthan’s “Gross National Happiness”, UNDP “Human Development Index”, NEF “Happy Planet Index, a bit more recent proposal by Fitoussi, Sen and Stiglitz, Polish ALK “Index of Balanced Socio-Economic Development” etc. All of them are elaborated in a “beyond GDP” paradigm and in a tradition of social indicators research. Some are limited to objective and subjective social conditions only, some other combine social and economic dimensions, using both survey data and social as well as economic statistics. There are several substantive and methodological problems of these indexes, such as ways of selecting particular simple indicators (index components), relevance of objective and subjective indicators (especially those obtained by social surveys), weighting, constructing “middle-level” indexes and analyzing their interrelations, defining “leading” and “lagging” indexes, checking reliability and validity, analyzing the trends, generalizing and interpreting the results, etc. The papers discussing some of these issues or similar problems of integrating subjective and objective survey data with official and other statistical data into more general indexes at international, national or sub-national level are invited. Both methodological and substantive papers may be accepted, but the preference will be given to papers dealing jointly with the methodology of index construction and the interpretation of obtained results.


Surveying Sensitive Issues: Challenges and Solutions 1 (O-101)

Convenor Mr Marc Hoeglinger (ETH Zurich)
Coordinator 1Professor Andreas Diekmann (ETH Zurich)
Coordinator 2Professor Ben Jann (University of Bern)

Surveying sensitive issues such as deviant behavior, stigmatizing traits, or controversial attitudes poses two challenges: The first challenge is data validity. Respondents are likely to misreport when asked sensitive questions, or they refuse answering such questions or even break off the interview. As a result, measurements are biased or incomplete. The second challenge is respondents’ privacy protection. Respondents’ data must be carefully protected to avoid leakage of sensitive personal information. Although this concerns almost all surveys in principle, it becomes much more important when, for instance, highly illegal behavior or political attitudes under repression are surveyed.

Switching to self-administrated survey modes such as online interviews mitigates undesired response effects to some extent. Also, adjusting the questionnaire design and the question wording might attenuate response effects. However, empirical results are inconclusive so far and results seem to depend highly on the particular issue and population surveyed. Providing respondents with full response privacy through indirect techniques such as the Randomized Response Technique or the Item Count Technique is a potential solution to both problems mentioned. However, albeit privacy is completely protected by these methods if properly implemented, respondents often lack understanding of and trust in these methods, so that misreporting might not be reduced.

In this session we invite submissions that deal with problems of surveying sensitive issues and/or present potential solutions. We are interested in studies that evaluate established methods such as indirect question techniques, but also in contributions that come up with novel strategies. Furthermore, we encourage submissions that deal with the concept of “sensitivity” and present theoretical frameworks and/or empirical analyses that shed light on the cognitive process of answering sensitive questions and “editing” responses. Submissions on statistical methods to analyze data from special questioning techniques are also welcomed.


Using Paradata to Improve Survey Data Quality 2 (HT-103)

Convenor Professor Volker Stocké (University of Kassel, Germany)
Coordinator 1Professor Jochen Mayerl (TU Kaiserslautern, Germany)
Coordinator 2Dr Oliver Lipps (Swiss Centre of Expertise in the Social Sciences (FORS), Lausanne, Switzerland)

“Paradata” are measures generated as a by-product of the survey data collection process. Prominent examples of paradata are data available from the sampling frame, call-record data in CATI surveys, keystroke information from CAI, timestamp files, observations of interviewer behavior or respondents’ response latencies (see Kreuter 2013 for an overview). These data can potentially be used to enrich questionnaire responses or to provide additional information about the survey (non-)participation process. In many cases paradata are available at no (or little) additional cost, but the theoretical basis for using paradata as indicator for survey data quality is very underdeveloped. Some examples about the use of paradata are:

Paradata in fieldwork monitoring and nonresponse research: Paradata are often used in the survey management context. With control charts survey practitioners can monitor fieldwork progress and interviewer performance. They are also indispensable in responsive designs as real-time information about fieldwork and survey outcomes which affect costs and errors. However, their role as indicator for interviewer or fieldwork effects, as well as predictors for nonresponse is unclear.

Paradata to understand respondent behavior: Paradata might aid assessing of the quality of survey responses, e.g. by means of response latencies or back-tracking. Research has used paradata to identify uncertainty in the answers given by respondents, e.g., if respondents frequently alter their answers. In this new strand of research, however, indicators might still be confounded and tap into multiple dimensions of the response process (e.g., response latencies may be an indicator for retrieval problems and/or satisficing).


Web-based Surveys and Mobile Devices (HT-105)

Convenor Professor Carsten Schröder (German Socio-Economic Panel Study (SOEP))
Coordinator 1Dr David Richter (German Socio-Economic Panel Study (SOEP))

According to figures from Germany's Federal Statistical Office, 51% of German Internet users are already using mobile devices to access the Internet.
The technical progress in communication technologies and their widespread use create new possibilities for collecting data in self-administered online surveys. Indeed, web-based surveys in combination with mobile devices like smart phones, tablet PCs, and so on are gaining rapidly in importance.
Lower costs, higher flexibility, and access to particular population subgroups are seen as the major advantages of these new technologies. At the same time, their use implies new challenges.
How should surveys be designed for these new technologies? Our session invites presentations that investigate how different devices may be combined and how they influence data quality. In particular, we welcome presentations that discuss the role of the use of a device in:
* survey errors
* self-selection
* response rates
* response patterns
* participation parameters (the number of completed questions, and the length of entries to open-ended questions)
* visual design
* survey administration


Weighting issues in complex cross-sectional and longitudinal surveys 1 (HT-102)

Convenor Ms Nicole Watson (University of Melbourne)
Coordinator 1Dr Olena Kaminska (University of Essex)

A range of issues arise when constructing weights for surveys with complex designs. Use of mixed modes or multiple frames in cross-sectional, longitudinal or cross-national surveys may result in uncertainty in selection probabilities, fieldwork outcomes or response propensities that make it difficult to construct appropriate weights. Further, longitudinal surveys tend to have greater uncertainty over time (as interviews are no longer attempted with some people). Growing complexity of design for multi-purpose surveys calls for the development of weighting methods to reflect them.

How should weights be best constructed in the presence of uncertainty about inclusion probabilities or fieldwork outcomes? How should the response process be best modeled in cross-national surveys where countries differ in quality and type of sampling frame and other auxiliary data? For surveys with multiple frames, how do we best construct weights that combine samples from multiple sources that may have partial overlap in the presence of uncertainty about membership? In constructing weights for longitudinal samples, we need to consider how populations are defined over time, how to treat deaths and other out-of-scopes, how best to adjust for attrition. Further, in household-based longitudinal surveys we need to determine how to best incorporate new sample members arising from changes in the household structure.

This session seeks to bring together survey methodologists involved in constructing weights for complex surveys (both longitudinal and cross-sectional) to explore the approaches taken. Papers submitted to this session might include comparisons of alternative methods, analysis of the impact of a particular component of the weights, or suggestions for new methods.


Assessing the Quality of Survey Data 3 (O-201)

Convenor Professor Joerg Blasius (University of Bonn)

This session will provide a series of original investigations on data quality in both national and international contexts. The starting premise is that all survey data contain a mixture of substantive and methodologically-induced variation. Most current work focuses primarily on random measurement error, which is usually treated as normally distributed. However, there are a large number of different kinds of systematic measurement errors, or more precisely, there are many different sources of methodologically-induced variation and all of them may have a strong influence on the “substantive” solutions. To the sources of methodologically-induced variation belong response sets and response styles, misunderstandings of questions, translation and coding errors, uneven standards between the research institutes involved in the data collection (especially in cross-national research), item- and unit non-response, as well as faked interviews. We will consider data as of high quality in case the methodologically-induced variation is low, i.e. the differences in responses can be interpreted based on theoretical assumptions in the given area of research. The aim of the session is to discuss different sources of methodologically-induced variation in survey research, how to detect them and the effects they have on the substantive findings.


Basic Human Values 3 (N-132)

Convenor Professor Eldad Davidov (University of Zurich)
Coordinator 1Dr Jan Cieciuch (University of Zurich and Cardinal Stefan Wyszyński University in Warsaw)
Coordinator 2Dr Constanze Beierlein (GESIS)

The 4th session organizer is Professor Peter Schmidt, peter.schmidt@sowi.uni-giessen.de, University of Giessen

Values have held an important position in the social sciences since their inception. Max Weber treated values as a central component in his analysis of capitalist society, linking the development of capitalism to the values of the Protestant Ethic. Values have played an important role not only in sociology, but in social psychology, anthropology, political science and related disciplines as well. They have been used to explain the motivational bases of attitudes and behavior and to characterize differences between both individuals and societies.

In 1992, Schwartz introduced a theory of ten basic human values, building on common elements in earlier approaches. The designers of the European Social Survey (ESS) chose this theory as the basis for developing a human values scale to include in the core of the survey. Recently, this theory has been extended to include 19 values (Schwartz et al., 2012) and a new scale, the PVQ-RR, has been developed to measure them.

In this session continuing work on basic human values as postulated by Schwartz will be presented. Presentations which discuss (1) The measurement of human values; (2) Values as predictors of attitudes, opinions or behaviour; (3) Value change; and related topics are welcome. Both substantive and methodological papers using cross-sectional, cross-cultural or longitudinal datasets are welcome.


Experimental designs in online survey research 3 (L-102)

Convenor Mr Henning Silber (Göttingen University)
Coordinator 1Mr Jan Karem Hoehne (Göttingen University)
Coordinator 2Professor Dagmar Krebs (Giessen University)

Experimental studies have become increasingly popular in survey research and are carried out in various disciplines such as sociology, political science, linguistics, economics and psychology. In survey research experimental designs are useful tools to get a better understanding of cognitive processes in order to give better practice advice for improving study and questionnaire design. In particular, the technological advances have made it significantly easier to use experimental designs in online field experiments as well as in computerized laboratory experiments.

This session invites presentations on empirical studies and theoretical discussions of experimental designs in online survey research.

- Empirical online research can include studies on response behavior and social desirability bias, as well as experiments on response rates and question design effects. Furthermore, we especially encourage presentations with replicated experimental results and welcome replications in different social contexts such as different cultural, educational and ethnic groups.
- Additionally, we invite presentations that discuss the value of experiments from a theoretical perspective. Theoretical presentations could contrast the merits and the limits of different forms of experimental study designs or provide a future outlook on the prospects of online experiments in survey research.

Presentations could cover the following research areas:

- Theory of experimental study designs
- Replication of experimental results
- Comparisons between different experimental designs (e. g., laboratory and field experiment)
- Split-ballot experiments (e. g., context effects, question order, response order, acquiescence, visual design effects, verbal effects)
- Choice experiments
- Laboratory experiments on response behavior (e. g., using eye tracking)
- Experiments with incentives
- Vignette studies
- Future prospects of experimental designs


Innovations in Computer-Assisted Data Collection (HT-103)

Convenor Ms Beth-ellen Pennell (Institute for Social Research, University of Michigan )
Coordinator 1Ms Patty Maher (Institute for Social Research, University of Michigan )
Coordinator 2Ms Gina Cheung (Institute for Social Research, University of Michigan )


This session (or sessions) will focus on the rapid diffusion of technology and new methods and approaches in automated data collection, including those being used in new and innovative ways in developing or transitional countries. Presentations may address methods and technologies used in data collection for quality monitoring, to reduce costs, make data available more quickly, or to expand measures using such technologies as biometric and biohaviometric devices. We welcome papers that highlight new technologies or older technologies being used in new contexts and new ways. For example, the collection and analysis of rich paradata (process data) is increasingly being used in very diverse settings, even in contexts with very little data collection infrastructure. Other examples of the use of technologies in new contexts include audio computer assisted interviewing, audio recording, digital photography, use of global positioning systems to add contextual data or as a quality control measure, satellite imaging to assist in sample selection, among many other possibly examples. Finally, future focused presentations that highlight methodological and technological challenges and opportunities for the field of survey methodology and survey practice are welcome.


Interviewers’ Deviations in Surveys 3 (O-202)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Professor Peter Winker (University of Giessen)

Interviewers’ behavior might have an impact on survey data. The session deals with deviations from the instructions when contacting and interviewing respondents. These deviations might be caused by different factors such as task difficulty, interviewers’ ability, experience and motivation, but also by the quality of questionnaires and instructions. Deviations might result in bias, but could also foster data quality, e.g. if interviewers try to help the respondents in providing a (correct) answer. The session aims to discuss both, deliberate (e.g. falsifications; providing explanation) and non-deliberate deviations (e.g. interviewers’ mistakes).
Researchers are invited to submit papers dealing with all kinds of interviewers’ deviations in the survey process which might result in non-observation or measurement errors but also positively influence survey outcomes. Of interest are theoretical approaches and empirical studies on detection and prevention, on explanatory factors and consequences of interviewers’ deviations. Thus, interviewers’ motivation to deviate from prescribed standards or to produce high quality survey data as well as interviewers’ cognitive skills and competencies could be of interest.


Large convenience samples, quantitative research and comparative analysis (O-206)

Convenor Mr Patrick Festy (National Institute for Demographic Studies, France)

Convenience sampling is often used in qualitative research where the objective is not to measure behaviors or opinions but to detect relationships between different phenomena. It is generally considered as non-scientific in quantitative research, despite some usage when surveyed populations are difficult or costly to reach and/or identify. It is nevertheless regaining popularity due to the development of online surveys where respondents are incented to answer freely accessible questionnaires. The massive number of respondents that can be easily obtained orientates towards quantitative analysis of the material, the more so as most questions are inevitably closed-ended. Even international comparisons of large samples become possible. An EU agency has recently attracted more than 90,000 respondents self identified as lesbians, gays, bisexuals or trans, in 28 countries, the largest sample ever assembled on this population. In a continent of 400,000,000 adults, the number of LGBT people is several millions and the selection bias in the sample risks to be massive, but who is able to resist the temptation of quantitative analysis of such a large and original material?
What is possible and impossible on such data? What lessons can be drawn from qualitative analysis methods, which could be relevant for large samples? Which is more or less biased: simple cross tabulations or more sophisticated analysis? Are meaningless national results open to meaningful cross-national comparisons?


Methodological developments in time use research (HT-104)

Convenor Miss Emily Gilbert (Centre for Longitudinal Studies, Institute of Education)
Coordinator 1Dr Stella Chatzitheochari (University of Warwick)

Providing a comprehensive and sequential account of daily activities and their context, time use data are increasingly utilised to produce national accounts of well-being, analyse a wide range of health and social outcomes, and understand different aspects of human behaviour. Recent years have witnessed the steady growth of stand-alone time use surveys, as well as the inclusion of time diary elements in large-scale social surveys. This has resulted in an impressive pool of data from developed and developing countries. However, despite this increased interest in the collection of time use data, there is relatively little recent methodological evidence in the area. The majority of earlier work focuses on conventional, paper-based diary formats that are becoming less common, while there is a lack of systematic research examining new modes of data collection and study designs.

This session aims to cover a range of contemporary methodological issues in time use research. In particular, submissions are welcomed on:
- using different modes of data collection and innovative technology for time use data collection, including the web and mobile phones
- designing time use diaries for children and young people including the design of age-specific activity categories and assessing the reliability and validity of children’s time diaries
- collecting and analysing time use data in longitudinal surveys
- innovative methods of statistical analysis of time use data
- effects of different modes of data collection, including comparisons of paper-based, web-based and App-based formats
- developments on harmonisation of cross-national time use data


New forms of data collection: mobile/web 1 (HT-105)

Convenor Dr Emanuela Sala (Dipartimento di Sociologia e Ricerca Sociale, Università di MIlano Bicocca)
Coordinator 1Dr Mario Callegaro (Google)
Coordinator 2Dr Teresio Poggio (Faculty of Economics and Management Free University of Bozen-Bolzano)

Advances in mobile and Internet technology offer researchers new tools, opportunities and challenges to design and carry out social surveys. The aim of this session is to foster discussion on the use of new forms of data collection in social research and its impact on data quality.


Survey data in composite indexes of well-being and socio-economic development 2 (N-131)

Convenor Professor Krzysztof Zagorski (Kozminski University)

There is a growing interest in composite indexes of well-being and socio-economic development, such as OECD “Better Life Index”, Kingdom of Buthan’s “Gross National Happiness”, UNDP “Human Development Index”, NEF “Happy Planet Index, a bit more recent proposal by Fitoussi, Sen and Stiglitz, Polish ALK “Index of Balanced Socio-Economic Development” etc. All of them are elaborated in a “beyond GDP” paradigm and in a tradition of social indicators research. Some are limited to objective and subjective social conditions only, some other combine social and economic dimensions, using both survey data and social as well as economic statistics. There are several substantive and methodological problems of these indexes, such as ways of selecting particular simple indicators (index components), relevance of objective and subjective indicators (especially those obtained by social surveys), weighting, constructing “middle-level” indexes and analyzing their interrelations, defining “leading” and “lagging” indexes, checking reliability and validity, analyzing the trends, generalizing and interpreting the results, etc. The papers discussing some of these issues or similar problems of integrating subjective and objective survey data with official and other statistical data into more general indexes at international, national or sub-national level are invited. Both methodological and substantive papers may be accepted, but the preference will be given to papers dealing jointly with the methodology of index construction and the interpretation of obtained results.


Surveying Sensitive Issues: Challenges and Solutions 2 (O-101)

Convenor Mr Marc Hoeglinger (ETH Zurich)
Coordinator 1Professor Andreas Diekmann (ETH Zurich)
Coordinator 2Professor Ben Jann (University of Bern)

Surveying sensitive issues such as deviant behavior, stigmatizing traits, or controversial attitudes poses two challenges: The first challenge is data validity. Respondents are likely to misreport when asked sensitive questions, or they refuse answering such questions or even break off the interview. As a result, measurements are biased or incomplete. The second challenge is respondents’ privacy protection. Respondents’ data must be carefully protected to avoid leakage of sensitive personal information. Although this concerns almost all surveys in principle, it becomes much more important when, for instance, highly illegal behavior or political attitudes under repression are surveyed.

Switching to self-administrated survey modes such as online interviews mitigates undesired response effects to some extent. Also, adjusting the questionnaire design and the question wording might attenuate response effects. However, empirical results are inconclusive so far and results seem to depend highly on the particular issue and population surveyed. Providing respondents with full response privacy through indirect techniques such as the Randomized Response Technique or the Item Count Technique is a potential solution to both problems mentioned. However, albeit privacy is completely protected by these methods if properly implemented, respondents often lack understanding of and trust in these methods, so that misreporting might not be reduced.

In this session we invite submissions that deal with problems of surveying sensitive issues and/or present potential solutions. We are interested in studies that evaluate established methods such as indirect question techniques, but also in contributions that come up with novel strategies. Furthermore, we encourage submissions that deal with the concept of “sensitivity” and present theoretical frameworks and/or empirical analyses that shed light on the cognitive process of answering sensitive questions and “editing” responses. Submissions on statistical methods to analyze data from special questioning techniques are also welcomed.


Surveys, ipsative and compositional data analysis (CODA) (HT-101)

Convenor Dr Berta Ferrer-rosell (University of Girona - Department of Economics)
Coordinator 1Dr Josep Daunis-i-estadella (University of Girona - Department of Computer Science, Applied Mathematics and Statistics)
Coordinator 2Professor Vera Pawlowsky-glahn (University of Girona - Department of Computer Science, Applied Mathematics and Statistics)

Statistical compositions are common in the chemical and biological analysis in the fields of geology and biology, among others. Typically the size is irrelevant and only the proportion or the relative importance of each component is of interest. In survey measurement, the so-called ipsative data also consist of positive data arrays with a fixed sum and which only convey information on the relative importance of each component. Examples include surveys measuring compositions of household budgets (% spent in each product category), time-use surveys (24-hour total), educational instruments allocating a total number of points into different abilities or orientations (e.g. Kolb’s learning styles or Boyatzis’ philosophical orientations), and social network compositions (% of family members, friends, neighbours, etc.)

Statistical analysis of compositional data is challenging because they lie in a restricted space and components cannot vary independently from one another ("all other things constant"): the relative importance of one component can only increase if the relative importance of at least one other component decreases. A popular solution is to transform compositional data by means of logarithms of ratios of components before applying standard analysis methods, while interpreting the results with great care.

Standard statistical methods such as ANOVA, linear regression and cluster analysis have a well documented tradition in compositional data analysis although there is room for improving the methods and make them friendlier to a wider audience. Less has been done regarding typical survey research analysis methods, for instance, multivariate analysis methods and latent-variable methods. The naive analysis of raw proportions is of common practice even if it is plagued with statistical problems (inconsistent inferences, heteroskedasticity, non-normality, censoring, perfect collinearity, and unclear interpretation, among others). The session aims to bridge methodological knowledge between the natural and social sciences in order to narrow this gap.


The New Data Sharing Environment: Increasing Options, Increasing Access 1? (O-106)

Convenor Dr Peter Granda (University of Michigan)

The New Data Sharing Environment: Increasing Options, Increasing Access?

Peter Granda
Inter-university Consortium for Political and Social Research (ICPSR)
University of Michigan

As social science funding agencies throughout the world place increasing emphasis on data sharing, both data producers and data repositories face new challenges. Data producers must fulfill public-access requirements when receiving funding awards. After their data are collected, they may be tempted to share the data themselves, but they often do not want the maintenance responsibility for the long term. Data repositories can offer the infrastructure and staff expertise to assist producers in meeting their responsibilities as good data stewards but must decide how much effort to expend to archive, curate, and preserve the increasing amounts of data being generated.

New options have appeared on the scene including data sharing sites like Dropbox and Figshare and “self-deposit” services hosted by social science data archives. These options offer a variety of mechanisms to deposit and publish data resources, different pricing models, and storage models that range from keeping the original bitstream for a definite period to a full preservation commitment including curation and migration of these files indefinitely.

This session brings data producers and data repositories together to present their views of the current and future data sharing environments. Key questions at this session:

• How do producers want to make to make their data available for secondary use?
• Should the output of data from all funding sources be preserved?
• Who decides which data files should be stored for the short term and which should receive permanent curation and preservation?
• Who should pay for the costs of data sharing? The funder, the person awarded the grant, national governments through their support of national archives, another entity?
• What types of repository structures best promote data access?


Weighting issues in complex cross-sectional and longitudinal surveys 2 (HT-102)

Convenor Ms Nicole Watson (University of Melbourne)
Coordinator 1Dr Olena Kaminska (University of Essex)

A range of issues arise when constructing weights for surveys with complex designs. Use of mixed modes or multiple frames in cross-sectional, longitudinal or cross-national surveys may result in uncertainty in selection probabilities, fieldwork outcomes or response propensities that make it difficult to construct appropriate weights. Further, longitudinal surveys tend to have greater uncertainty over time (as interviews are no longer attempted with some people). Growing complexity of design for multi-purpose surveys calls for the development of weighting methods to reflect them.

How should weights be best constructed in the presence of uncertainty about inclusion probabilities or fieldwork outcomes? How should the response process be best modeled in cross-national surveys where countries differ in quality and type of sampling frame and other auxiliary data? For surveys with multiple frames, how do we best construct weights that combine samples from multiple sources that may have partial overlap in the presence of uncertainty about membership? In constructing weights for longitudinal samples, we need to consider how populations are defined over time, how to treat deaths and other out-of-scopes, how best to adjust for attrition. Further, in household-based longitudinal surveys we need to determine how to best incorporate new sample members arising from changes in the household structure.

This session seeks to bring together survey methodologists involved in constructing weights for complex surveys (both longitudinal and cross-sectional) to explore the approaches taken. Papers submitted to this session might include comparisons of alternative methods, analysis of the impact of a particular component of the weights, or suggestions for new methods.


Advanced survey estimation methods for treatment of non-sampling errors 1 (HT-101)

Convenor Dr Alina Matei (University of Neuchatel, Switzerland)
Coordinator 1Professor Giovanna Ranalli (University of Perugia, Italy)

Non-sampling errors can be generated by nonresponse, frame imperfections, measurement and data processing errors. We focus here on nonresponse and coverage errors as a possible source of non-negligible bias. Nonresponse is determined by the failure to obtain fully or partially information from the sampled units. Coverage or frame errors are caused by the gap between the target population and the sampling frame.

The proposed session will bring together presentations proposing advanced estimation methods for treatment of these types of non-sampling errors. The presentations will focus on methodologies to deal with nonresponse, frame imperfections or both. Methods using propensity score methods or (generalized) calibration to handle nonresponse, estimation methods for multiple-frame sampling, joint calibration for nonresponse and frame imperfections, calibration in the presence of domain misclassification, etc. are invited to be submitted in this session.


Enhancing survey data with geocoded auxiliary data 1 (HT-103)

Convenor Dr Sarah Butt (City University London)
Coordinator 1Mr Rory Fitzgerald (City University London)
Coordinator 2Ms Kaisa Lahtinen (City University London)

Combining survey data with auxiliary data from other sources provides researchers with a wealth of potential opportunities to improve survey data collection and the quality of the inferences that can be drawn from survey data. One type of auxiliary data that is increasingly widely available is geocoded data i.e. data that can be linked to survey data based on the geographic location of sampled addresses. This includes census data, administrative data from government agencies and other public sector bodies, commercial databases and geospatial maps. Such data can be used to answer substantive research questions about the effect of location on attitudes and behaviour. By providing information about all sample units, geocoded data are also a potentially valuable tool to aid data collection and for overcoming non-response bias.

However, using auxiliary data from pre-existing sources presents a number of challenges.
Identifying suitable auxiliary variables that are correlated with the survey variables of interest (and, in the case of non-response analysis, response propensity) can be difficult. There are concerns over the coverage, accuracy and timeliness of external databases, the extent to which data which is often highly aggregated can characterise sampled households, and the increased likelihood of deductive disclosure as a result of combining different data sources.

This session invites studies that have combined survey data with geocoded auxiliary data to share their learning regarding the opportunities and challenges associated with this approach. We are interested in papers that provide insights into any of the following:
• The pros and cons of using different sources of geocoded auxiliary data
• Strategies for linking geocoded auxiliary data to survey data
• Modelling item or unit non-response using auxiliary data
• Combining auxiliary data and survey data cross-nationally


European Values Study 1 (N-132)

Convenor Dr Ruud Luijkx (Tilburg University )

The European Values Study (EVS) is a unique research project into Europe’s basic values. First, it spans a period of almost 30 years with surveys in 1981, 1990, 1999, and 2008. Second, EVS has an extensive geographical coverage. In Europe, the survey has gradually been expanded from mostly Western European countries in 1981 to the whole of Europe in 2008. Third, even though several items have been changed in the consecutive waves, EVS still includes an impressive number of unchanged questions. Finally, and perhaps most importantly, the questionnaires pertain to a very broad spectrum of life domains: family and marriage, economics, work, leisure, politics, religion, morality. This allows to introduce domain-specific and overarching concepts and to examine the relationships between basic values and attitudes in different fields. Such a rich data source also offers a unique chance for substantive and methodological investigations. We are particularly interested in papers which make use of the comparative potential of EVS from a methodological and a substantive perspective. To give a few examples: Do the measurement instruments that have been used in EVS guarantee comparability across time and space? How accessible is this huge data base? What are the basic empirical findings on long-term change and what are the main cross national differences? How are the specific domain values related to each other and to the overarching concepts? How does one carry out such analyses? What are the main problems? However, other empirical and methodological topics are possible too. Researchers are invited to submit paper proposals for this session on EVS.


Experimental designs in online survey research 4 (L-102)

Convenor Mr Henning Silber (Göttingen University)
Coordinator 1Mr Jan Karem Hoehne (Göttingen University)
Coordinator 2Professor Dagmar Krebs (Giessen University)

Experimental studies have become increasingly popular in survey research and are carried out in various disciplines such as sociology, political science, linguistics, economics and psychology. In survey research experimental designs are useful tools to get a better understanding of cognitive processes in order to give better practice advice for improving study and questionnaire design. In particular, the technological advances have made it significantly easier to use experimental designs in online field experiments as well as in computerized laboratory experiments.

This session invites presentations on empirical studies and theoretical discussions of experimental designs in online survey research.

- Empirical online research can include studies on response behavior and social desirability bias, as well as experiments on response rates and question design effects. Furthermore, we especially encourage presentations with replicated experimental results and welcome replications in different social contexts such as different cultural, educational and ethnic groups.
- Additionally, we invite presentations that discuss the value of experiments from a theoretical perspective. Theoretical presentations could contrast the merits and the limits of different forms of experimental study designs or provide a future outlook on the prospects of online experiments in survey research.

Presentations could cover the following research areas:

- Theory of experimental study designs
- Replication of experimental results
- Comparisons between different experimental designs (e. g., laboratory and field experiment)
- Split-ballot experiments (e. g., context effects, question order, response order, acquiescence, visual design effects, verbal effects)
- Choice experiments
- Laboratory experiments on response behavior (e. g., using eye tracking)
- Experiments with incentives
- Vignette studies
- Future prospects of experimental designs


Global Societal Change (L-101)

Convenor Dr Tom W. Smith (NORC at the University of Chicago)

This session examines societal change using major cross-national datasets such as the Comparative Study of Electoral Systems, the East Asian Social Survey, the European Social Survey, the International Social Survey Program, and the World Values Survey. Special focus is on the 1) impact of globalization on attitudes and behaviors across countries, 2) whether there are signs of convergence, and 3) the role of cohort turnover in shaping global societal change.


How do interviewers influence data? (O-202)

Convenor Miss Claudia Karwath (Leibniz Institute for Educational Trajectories)
Coordinator 1Miss Manja Attig (Leibniz Institute for Educational Trajectories)

There are various modes of data collection, such as telephone, face-to-face or online. Some of these modes include the use of interviewers, which play a special role in the study organization. For example, they have to contact and motivate the respondent for participation. In this case, interviewers not only can influence the collecting data process (e.g., finding the right respondent) but furthermore they can affect data quality in different ways as well (e.g., influencing the response of the participants).

To organize studies, especially with different modes of data collection, it is important to involve possible effects of using interviewers.

Therefore, the following session focus on topics such as:

- Interviewer characteristics and their influence on data
- Interviewer-respondent interactions
- Effects of different modes of data collection


Intra-EU immigration: new form of migration, new challenges for survey methodology? (L-103)

Convenor Professor Céline Teney (University of Bremen)
Coordinator 1Professor Laurie Hanquinet (The University of York)

Since the Maastricht treaty and the right of free movement, EU countries have been facing a growing wave of intra-EU migration. In contrast to the classical immigration waves –such as the guest workers in the 60´s and 70´s, recent intra-EU migrants tend to be highly mobile and skilled. This new form of migration has been receiving increasingly more attention from the scientific community. Above all, case and qualitative studies have boomed during the last years. By contrast, quantitative sociology –with a few exceptions- has largely overlooked this new migration phenomenon. This neglect is mainly due to the difficulty of identifying intra-EU immigrants in the receiving countries and the resulting challenges of drawing representative large-N samples of recent intra-EU movers. Indeed, EU citizens have the right to cross national borders without any registration obligations. This implies that most of the selection procedures traditionally used for sampling classical immigrants are obsolete for this new migration wave. How can we capture this freedom of move? And how can we represent and possibly map it?

With this panel, we hope to bring together quantitative sociologists who seek to study this new form of migration. We would like to discuss innovative strategies for drawing representative samples of these intra-EU migrants, these EU citizens who decide to live in another EU country, but also new exciting techniques to account for this freedom of move. We are, for instance, interested in visual techniques to map EU migrants’ movements. We are therefore welcoming contributions that present ways of sampling this specific population. Contributors are invited not only to shed light on the strengths and advantages of sampling strategies but also to discuss the shortcomings, sampling difficulties and representativity of the sample.


Measurement errors in official statistical surveys (O-201)

Convenor Mr Anton Karlsson (Statistics Iceland)
Coordinator 1Mr Øyvin Kleven (Statistics Norway)

National Statistical Institutes (NSI’s) in the European Statistical System have traditionally not focused on survey measurement error. There is therefore a lack of knowledge in the system on the spread, amount and influence of measurement error on the results of surveys conducted by the NSI’s in the system. This lack of knowledge prevents survey methodologists from applying relevant methods or best practices in order to deliver high-quality data that has been thoroughly checked with regards to effects of measurement error. It is therefore important to provide a venue for survey methodologists working on minimizing measurement errors in NSI-surveys for them to present their work, exchange ideas and study new methods and techniques. The issue of measurement error in NSI surveys has become especially relevant with the emergence of newer modes of data collection (e.g. web-questionnaires) and the use of multiple modes within a single survey. We therefore propose to organize a session for the ESRA 2014 conference in Reykjavik, Iceland where the focus will be on measurement error in official statistical surveys, e.g.: 1) Pretesting survey instruments used in NSI-surveys and its effectiveness in reducing measurement error; 2) cross-national comparisons of items in order to assess their comparability over different countries; 3) measurement effects due to the use of different modes in NSI surveys; 4) methods and practices for monitoring measurement error in ongoing surveys; 5) Post-survey corrections for measurement error in NSI surveys; 6) The cross-national comparability of output harmonized surveys.


Multi-actor surveys (O-206)

Convenor Mrs Inge Pasteels (University of Antwerp, Belgium)

For this session researchers are invited to submit papers considering a particular survey methodological topic within the context of multi-actor surveys. Recently multi-actor surveys came up as a new type of surveys besides individual and household surveys. In surveys with a multi-actor design, several individuals who are related to each other by precisely defined social ties, are involved. All individuals together with the well-defined social relationships and social roles constitute the multi-actor unit. Several types of multi-actor surveys can be distinguished according to the sampling unit. If the sampling unit corresponds with only one directly selected individual around which the remaining multi-actor pattern will be built, survey data are considered as being “singular multi-actor data”. If several persons are directly sampled, survey data are “multiple multi-actor data”. In case of two directly sampled individuals, we refer to this type of survey data as “dyadic multi-actor data”. Furthermore, several settings can be approached by a multi-actor survey, e.g. families with members living in different households, an educational system with pupils, teachers and parents as the main actors or labor force settings with employers and employees. Papers in this session can deal with a wide range of survey methodological issues as sampling, fieldwork processes and fieldwork monitoring, item and unit nonresponse, weighting and imputation, interviewer effects and interviewer training, mixed mode designs,…. but highlighting specificities of well-known techniques, procedures, terminology,… given the multi-actor survey design has to be the main goal of the paper.


New forms of data collection: mobile/web 2 (HT-105)

Convenor Dr Emanuela Sala (Dipartimento di Sociologia e Ricerca Sociale, Università di MIlano Bicocca)
Coordinator 1Dr Mario Callegaro (Google)
Coordinator 2Dr Teresio Poggio (Faculty of Economics and Management Free University of Bozen-Bolzano)

Advances in mobile and Internet technology offer researchers new tools, opportunities and challenges to design and carry out social surveys. The aim of this session is to foster discussion on the use of new forms of data collection in social research and its impact on data quality.


Potentials and constraints of weighting to improve survey quality (HT-102)

Convenor Dr Stephanie Steinmetz (University of Amsterdam)
Coordinator 1Professor Kea Tijdens (University of Amsterdam)

As scientific surveys are indispensable instruments of social research, their results can impact significantly on public opinion formation and official decision making. Therefore, the accuracy of a survey is of paramount importance. However, it is determined by many aspects of the survey process, including sampling, patterns of response and non-response as well as survey design and data collection procedures.
The introduction of the web as a new mode of data collection, however, has triggered a heated debate on their scientific validity and the degree to which their results can be generalised for the whole population – in particular for non-probability web surveys. To deal with problems arising from sample biases, it has been emphasised that weighting procedures are necessary for generalising web survey results for the whole population, even though particularly the implications of propensity score or other advanced adjustment techniques are still under discussion. As the application of such adjustment procedures has produced rather diverse results, it is not entirely clear whether the representativeness of web surveys can be improved through weighting.
The session aims to evaluate the potentials and constraints of different adjustment procedures to improve survey quality. Papers are invited which address the methodological foundation of different adjustment techniques, and provide insights into their simple and advanced application for offline and online surveys. Contributors are particularly encouraged to explore, compare and critically discuss the efficiency of different weighting procedures to improve survey quality.


The impact of questionnaire design on measurements in surveys 1 (HT-104)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Ms Kathrin Bogner (GESIS)

Questionnaire design is crucial for obtaining high-quality survey data. Still, there is a great need for research that helps to better understand how and under which conditions different design aspects of questionnaires impact measurement process and survey data quality. Therefore, researchers are invited to submit papers dealing with questionnaire design features such as question wording, visual design and answer formats, instructions, introductions and other relevant design aspects of questionnaires. Also, different means of measurement such as questions with nominal answer categories, rankings, ratings, sematic differentials or vignettes can be addressed or can be matter of comparison. Of interest is the impact of questionnaire design on response behavior, on systematic as well as non-systematic error or on validity. In addition, respondents’ cognition or motivation can be in focus of the studies.


The New Data Sharing Environment: Increasing Options, Increasing Access 2? (O-106)

Convenor Dr Peter Granda (University of Michigan)

The New Data Sharing Environment: Increasing Options, Increasing Access?

Peter Granda
Inter-university Consortium for Political and Social Research (ICPSR)
University of Michigan

As social science funding agencies throughout the world place increasing emphasis on data sharing, both data producers and data repositories face new challenges. Data producers must fulfill public-access requirements when receiving funding awards. After their data are collected, they may be tempted to share the data themselves, but they often do not want the maintenance responsibility for the long term. Data repositories can offer the infrastructure and staff expertise to assist producers in meeting their responsibilities as good data stewards but must decide how much effort to expend to archive, curate, and preserve the increasing amounts of data being generated.

New options have appeared on the scene including data sharing sites like Dropbox and Figshare and “self-deposit” services hosted by social science data archives. These options offer a variety of mechanisms to deposit and publish data resources, different pricing models, and storage models that range from keeping the original bitstream for a definite period to a full preservation commitment including curation and migration of these files indefinitely.

This session brings data producers and data repositories together to present their views of the current and future data sharing environments. Key questions at this session:

• How do producers want to make to make their data available for secondary use?
• Should the output of data from all funding sources be preserved?
• Who decides which data files should be stored for the short term and which should receive permanent curation and preservation?
• Who should pay for the costs of data sharing? The funder, the person awarded the grant, national governments through their support of national archives, another entity?
• What types of repository structures best promote data access?


The use of survey data to study well-being and economic outcomes (N-131)

Convenor Mr Francesco Sarracino (STATEC, HSE-LCSR)
Coordinator 1Ms Chiara Peroni (STATEC)
Coordinator 2Mr Cesare Riillo (STATEC)

Despite the popularity of well-being measures in economic studies, the relation between subjective well-being and economic performance is still an open issue.

Several empirical studies based on survey data collected on individuals suggest that happier people are more productive and more committed to their work. Happier workers are more pragmatic, less absent, more cooperative and friendly (Bateman and Organ, 1983; Judge et al., 2001) change their job less often and they are more accurate and willing to help others (Spector, 1997). Moreover, happier people earn more money and have better relationships with colleagues and clients, all aspects that contribute to work productivity (George and Brief, 1992; Pavot and Diener, 1993; Wright and Cropanzano, 2000). These results have been confirmed also in experimental settings (Oswald et al., 2009). Further evidence suggests that increased life satisfaction has a positive impact on firms’ economic outcomes (Edmans, 2012).


However, the evidence on the relation between well-being and economic performance is not conclusive. For example, this literature would benefit from new analysis linking survey data to auxiliary data sources on economic outcomes as well as from widening the scope of economic indicators used (Dimaria et al. 2014).

This session aims at collecting contributions analysing the role of well-being and/or job satisfaction on economic outcomes.
We welcome applications on life satisfaction, job satisfaction, productivity, entrepreneurship, innovation, employment, inequality, economic growth.


4th organizer: Dr. Wladimir Raymond, Wladimir.Raymond@statec.etat.lu, STATEC, Luxembourg


Advanced survey estimation methods for treatment of non-sampling errors 2 (HT-101)

Convenor Dr Alina Matei (University of Neuchatel, Switzerland)
Coordinator 1Professor Giovanna Ranalli (University of Perugia, Italy)

Non-sampling errors can be generated by nonresponse, frame imperfections, measurement and data processing errors. We focus here on nonresponse and coverage errors as a possible source of non-negligible bias. Nonresponse is determined by the failure to obtain fully or partially information from the sampled units. Coverage or frame errors are caused by the gap between the target population and the sampling frame.

The proposed session will bring together presentations proposing advanced estimation methods for treatment of these types of non-sampling errors. The presentations will focus on methodologies to deal with nonresponse, frame imperfections or both. Methods using propensity score methods or (generalized) calibration to handle nonresponse, estimation methods for multiple-frame sampling, joint calibration for nonresponse and frame imperfections, calibration in the presence of domain misclassification, etc. are invited to be submitted in this session.


Determinants of subjective well-being or dimensions of quality of life? (N-131)

Convenor Mr Francesco Sarracino (STATEC, Luxembourg)
Coordinator 1Ms Malgorzata Mikucka (Universite catholique de Louvain)

The literature distinguishes mainly two approaches to measuring well-being. The first one is adopted by institutions and policy-oriented bodies that adopt multidimensional indexes of quality of life. Such indexes supplement the more commonly used income-based measures of well-being and allow a detailed description of living conditions and an assessment of societies’ progress in achieving citizens’ quality of life.

The second approach considers subjective well-being measured with a single variable, usually life satisfaction or happiness, and investigates its economic and non-economic determinants.

These two approaches treat differently the same set of variables. For example, income or health would be regarded as dimensions of quality of life in the first approach, but they would be seen as determinants of subjective well-being in the second approach.

This session invites analyses of advantages, disadvantages, and implications of the choice between the two approaches to measuring well-being. We invite papers addressing the following and related questions:
(1) Are there any ways to empirically assess the correctness of each of the two approaches? Can we test if a factor should be treated as an outcome (i.e. a dimension of quality of life) or rather as a determinant of subjective well-being?
(2) What is the relationship between the single measure of subjective well-being and the multiple dimensions of quality of life?
(3) Policy-oriented initiatives propose lists of dimensions of quality of life, but do we actually need multiple indicators? How to make sense of multidimensional indexes of well-being?
(4) Which lessons about well-being can we learn by using each of these approaches?


Enhancing survey data with geocoded auxiliary data 2 (HT-103)

Convenor Dr Sarah Butt (City University London)
Coordinator 1Mr Rory Fitzgerald (City University London)
Coordinator 2Ms Kaisa Lahtinen (City University London)

Combining survey data with auxiliary data from other sources provides researchers with a wealth of potential opportunities to improve survey data collection and the quality of the inferences that can be drawn from survey data. One type of auxiliary data that is increasingly widely available is geocoded data i.e. data that can be linked to survey data based on the geographic location of sampled addresses. This includes census data, administrative data from government agencies and other public sector bodies, commercial databases and geospatial maps. Such data can be used to answer substantive research questions about the effect of location on attitudes and behaviour. By providing information about all sample units, geocoded data are also a potentially valuable tool to aid data collection and for overcoming non-response bias.

However, using auxiliary data from pre-existing sources presents a number of challenges.
Identifying suitable auxiliary variables that are correlated with the survey variables of interest (and, in the case of non-response analysis, response propensity) can be difficult. There are concerns over the coverage, accuracy and timeliness of external databases, the extent to which data which is often highly aggregated can characterise sampled households, and the increased likelihood of deductive disclosure as a result of combining different data sources.

This session invites studies that have combined survey data with geocoded auxiliary data to share their learning regarding the opportunities and challenges associated with this approach. We are interested in papers that provide insights into any of the following:
• The pros and cons of using different sources of geocoded auxiliary data
• Strategies for linking geocoded auxiliary data to survey data
• Modelling item or unit non-response using auxiliary data
• Combining auxiliary data and survey data cross-nationally


Factorial survey experiments (L-102)

Convenor Dr Edurne Bartolome Peral (University of Deusto)

Experimental designs, and factorial surveys in particular, have become very popular in the study of social relations and social processes in the last years. Factorial Survey consits in presenting repeated hypothetical situations, containing a number of variations,which respondents need to judge or decide on. In addition to the situation, key information on respondents is also collected and analyzed.

As the topics and contexts covered by this methodology are also growing very fast, many issues regarding application, topics, problems, particular groups or samples etc. arise during the process of such researches.

The main aim of this session is to share and present:

1.- Different applications of this methodology in social sciences

2.- Improvements and challenges of the use of the methodology in specific contexts or situations.

3.- Pariticularities of this methodology in dealing with specific groups


Global societal change 2 (L-101)

Convenor Mr Ferruccio Biolcati Rinaldi (University of Milan)
Coordinator 1Mr Cristiano Vezzoni (University of Trento)

This session examines societal change using major cross-national datasets such as the Comparative Study of Electoral Systems, the East Asian Social Survey, the European Social Survey, the International Social Survey Program, and the World Values Survey. Special focus is on the 1) impact of globalization on attitudes and behaviors across countries, 2) whether there are signs of convergence, and 3) the role of cohort turnover in shaping global societal change.


Investigating Survey Fieldwork Processes: Interviewers and Their Strategies (O-202)

Convenor Dr Wojciech Jablonski (University of Lodz)

This session invites presentations dealing with different aspects of fieldwork in interview surveys – both in person (PAPI/CAPI) and over the telephone (CATI). In particular, we are interested in two issues. On the one hand, we will focus of the fieldwork procedures, guidelines, sets of rules, etc. implemented in order to keep the research process standardized and achieve high quality of survey data. On the other, we will investigate the problem of complying with these principles during fieldwork.

Topics that might come under this theme include (but are not limited to):
- innovative practices in interviewers' qualification and training (general, project-specific, and refresher);
- procedures of monitoring and evaluating interviewers’ job performance (in particular, detecting interviewers' deviations);
- analysis of interviewers’ behaviour during survey introduction and while asking questions/recording answers;
- interviewers’ attitude toward their job (specifically the difficulties they encounter while administering the survey, and the solutions they implement in order to overcome these problems).


Lay and co-researchers in survey research - participatory survey design (O-206)

Convenor Dr Dirk Schubotz (ARK, Queen's University Belfast)
Coordinator 1Dr Ingvill Mochmann (GESIS-Leibniz Institute for the Social Sciences)

Traditionally, participatory research projects which involve lay people as co-researchers or peer researcher have used qualitative and interpretive methods, such as focus groups, interviews or action research methods. The role of lay people in survey research, which is often regarded as very technical and perhaps too demanding for anyone without a related academic background, has rarely been extended beyond the function of piloting questions. However, with an increasingly active role of advocacy groups, and with policy regulations in many European countries that require decision makers to involve clients in the improvement of welfare services, there has been a growing scope to involve lay researchers in survey design. Examples for this are health research, children's rights based research and research involving older people. Lay people have been involved in research advisory groups, but also directly in the drafting of questions, the data collection, analysis and dissemination - and in rare cases, the actual design of the study.

For this session we invite papers that report on empirical experiences of involving lay people in any aspect of survey research. We also invite papers discussing thoughts and challenges of lay researcher involvement in survey research from a more theoretical and epistemological perspective.


Measurement errors in the wealth surveys 1 (O-201)

Convenor Mr Junyi Zhu (Deutsche Bundesbank)
Coordinator 1John Sabelhaus (Federal Reserve Board)
Coordinator 2Brian Bucks (Consumer Financial Protection Bureau)

Obtaining a comprehensive picture of households’ balance sheets and understanding their wealth accumulation process is of increasing interest to a large audience ranging from poli-cymakers and researchers to the general public. Consequently, more and more wealth surveys have been established worldwide. However, wealth data are susceptible to measurement errors specific to the nature of various asset and liability items. For example, households may not assess the value and amount of their assets constantly. And the valuation of less traded or distinctive assets is not straightforward. The knowledge required to answer some question can be demanding. Financial topics are always sensitive. Typically, questions on ownership of assets or liabilities are answered more accurately than questions on their value and in most cases the reporting quality of the debts outperforms that of the assets. Households from both ends of the wealth distribution are hard to identify and reach. The longitudinal data adds another layer of difficulty in distinguishing true changes from measurement errors. On the other hand, reporting error, the main measurement error, does not have a homogeneous pattern but can be classified.
We would like to invite survey practitioners to discuss how to detect and tackle measurement errors in wealth surveys. Researchers can analyze the missing pattern within the survey as a signal of potential errors. Matching to external surveys or administrative data and utilizing the panel dimension are other options to gauge the plausibility of answers. But then, there have been many prevention and reconciling measures. They include careful design and sequencing of questions, specialized interviewer training, software real-time checks, editing by reviewing the comments, dependent interviewing, etc. Innovative approaches are especially welcome. For example, using tax records, property lien data, online finance websites or other sources can fill the gap in building comprehensive profile of wealth accumulation.


Modelling unit nonresponse and attrition processes 1 (HT-102)

Convenor Ms Carina Cornesse (GIP, Mannheim University)
Coordinator 1Dr Gabriele Durrant (School of Social Sciences, University of Southampton)
Coordinator 2Professor Annelies Blom (GIP, Mannheim University)

This session focuses on analysing the processes leading to unit nonresponse in cross-sectional and attrition in longitudinal data. Unit nonresponse and attrition are major issues affecting data quality in surveys. Their importance has increased over the past decades as response rates in the US and Europe have been decreasing across survey modes and nonresponse rates may be related to nonresponse bias.

When modelling the fieldwork processes leading to nonresponse, research can draw on auxiliary data sources. These may include paradata, such as call record data, interviewer observations, time stamps during the interview, or variables from external data sources, such as administrative, register and census data.

In recent years, the statistical techniques that have been developed to model unit nonresponse and attrition and applied to survey data have become increasingly sophisticated. In addition, both ex-post modelling to learn from previous fieldwork outcomes and real-time modelling to inform adaptive and responsive survey designs have found its way into the survey methodological realm.

For our session we invite submissions from researchers who model unit nonresponse and attrition processes. We specifically encourage submissions of papers that use auxiliary data to model unit nonresponse and attrition processes and papers that use complex statistical models for this purpose.


New forms of data collection: mobile/web 3 (HT-105)

Convenor Dr Emanuela Sala (Dipartimento di Sociologia e Ricerca Sociale, Università di MIlano Bicocca)
Coordinator 1Dr Mario Callegaro (Google)
Coordinator 2Dr Teresio Poggio (Faculty of Economics and Management Free University of Bozen-Bolzano)

Advances in mobile and Internet technology offer researchers new tools, opportunities and challenges to design and carry out social surveys. The aim of this session is to foster discussion on the use of new forms of data collection in social research and its impact on data quality.


Social Desirability and Non-Reactive Methods in Survey Research: Improving Theory and Data Collection 2 (O-101)

Convenor Dr Ivar Krumpal (University of Leipzig)
Coordinator 1Professor Roger Berger (University of Leipzig)
Coordinator 2Professor Mark Trappmann (IAB Nürnberg)

Social desirability bias is a problem in surveys collecting data on private or norm-violating issues (e.g. sexual behavior, health related issues, voting preferences, income, or unsocial opinions) as soon as the respondent’s true score differs from his or her perception of the social desirable score. Due to the respondents’ strive for social approval and keeping a favourable self-image as well as data protection concerns, collecting valid data on private or norm-violating issues is a challenging task. More specifically, respondents may engage in impression management or self-deception or edit their answer before reporting it. Non-reactive data collection methods could improve measurements and data quality in surveys where social desirability bias is a potential problem. Therefore, the possibilities and limits of non-reactive methods (e.g. record linkage approaches, surveys without questions, biomarkers, field experiments or administrative data usage) will be critically discussed and compared to methods which are based on self-reports.

This session has four main goals: (1) discussion of the theoretical foundation of the research on social desirability bias in the context of a general theory of human psychology and social behavior. A clearer understanding of the social interactions between the actors that are involved in the data collection process could provide empirical researchers with a substantiated basis for optimizing their survey design and data collection to achieve high quality data; (2) presentation of current empirical research focusing on non-reactive methods of data collection in connection with the problem of social desirability; (3) discussion of new designs combining or contrasting non-reactive methods with standard ‘question-and-answer’ survey measurement in innovative ways; (4) exploration of possibilities of integrating such new and innovative approaches in well-established, large-scale population surveys taking into account problems of research ethics and data protection.


Social science data harmonization and replication: challenges and solutions for the 21st century (O-106)

Convenor Dr Kristi Winters (GESIS - Leibniz Institute for the Social Sciences)

Statistical analyses often require extensive data preparation and variable harmonization before the research can begin, yet there are no set documentation standards to facilitate transparent and precise replication. Second, increasing numbers of academic journals are adopting data policies to facilitate transparency and replication. This move to best practices increases the burden on researchers to make their data preparation, harmonization and variable transformation work transparent. Third, researchers have crossed the threshold into a digital world where, every day, humans create 2.5 quintillion bytes of data. This has led to a proliferation in datasets and the digital age has made accessing and combining data from multiple sources easier than ever. While this is a tremendous boom to social research, it further increases the need for transparency in variable transformations and harmonizations. All of this comes at a time when research journals space or stylistic constraints result in the omission of methodological details. This panel invites papers that address the challenges - and opportunities - the age of 21st century digital data present to social scientists. Paper topics may include, but are not limited to, issues of replication and replicability, documenting data preparation and variable harmonizations, trends in journal data policies, and resources for documenting data preparation for publication purposes and journal data policies.


Survey Research in Developing Countries 1 (L-103)

Convenor Dr Irene Pavesi (Small Arms Survey)

This session explores the challenges involved in conducting survey research in developing countries and discuss best practices in sampling, questionnaire design and fieldwork organisation.

Even more often than in developed countries up-to-date data on population size and composition is absent. Mobile populations, scarcely populated areas and areas connected only by low quality roads and security issues complicate the creation of a sampling frame. What strategies have researchers used to deal with these challenges?

Response rates tend to be high in developing countries. This is in part because in rural areas trust tends to be high or a survey is seen as an interesting break from everyday life. However in some cases the consent of village heads or other local leaders is an order to people to participate. How does this fit with the idea of informed consent?

High poverty in some areas raises ethical questions on whether and how respondents should be compensated for their time; if respondents receive cash or in kind compensation this can lead to competition among households for inclusion in the survey. What are appropriate ways to compensate respondents?

Large household with complex structures can make collection of household data a time consuming and error prone process. How can data be collected in an efficient way?

High ethnic and linguistic diversity poses challenges to both questionnaire translation and selection of interviewers. How can these challenges be dealt with?

If the people who design the questionnaire are not from the country of data collection, what procedures can be used to ensure that concepts in the survey resonate with those of the target population?

We welcome papers on these and related topics, such as reaching female respondents, use of ICT in data collection, surveying in (post-)conflict areas, and surveys among populations with high illiteracy rates


The impact of questionnaire design on measurements in surveys 2 (HT-104)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Ms Kathrin Bogner (GESIS)

Questionnaire design is crucial for obtaining high-quality survey data. Still, there is a great need for research that helps to better understand how and under which conditions different design aspects of questionnaires impact measurement process and survey data quality. Therefore, researchers are invited to submit papers dealing with questionnaire design features such as question wording, visual design and answer formats, instructions, introductions and other relevant design aspects of questionnaires. Also, different means of measurement such as questions with nominal answer categories, rankings, ratings, sematic differentials or vignettes can be addressed or can be matter of comparison. Of interest is the impact of questionnaire design on response behavior, on systematic as well as non-systematic error or on validity. In addition, respondents’ cognition or motivation can be in focus of the studies.


Poster Submission (HT-101)

Convenor Professor Bart Meuleman (University of Leuven)


Long-Term Cross-National Assessment of Social Cohesion (N-131)

Convenor Professor Klaus Boehnke (Jacobs University Bremen)

Cohesion as a social indicator reflecting the quality of contemporary societies is a topic of increasing importance in times of globalization and a significant increase in migration flows around the world. Several different conceptualizations of social cohesion have been offered in the literature, but a comprehensive empirical assessment of social cohesion across time and in various regions of the world has not been provided yet. Recently Bertelsmann Foundation commissioned an attempt to provide a benchmarking concept and a secondary data-analytic approach to assessing social cohesion in the OECD world since 1989. Conceptually, the Bertelsmann project defines social cohesion as a multidimensional characteristic of a collective measured at the micro, meso, and macro levels on nine dimensions, namely social network quality, trust in people, acceptance of diversity, identification with the social entity, trust in institutions, perceived fairness, solidarity and helpfulness, respect for social rules, and magnitude of civic participation. Empirically the study had Scandinavian countries emerge at the top of the social cohesion ranking and South-Eastern European states at the bottom among 34 countries. Bertelsmann also commissioned an analysis on the development of social cohesion in the 16 German states since the fall of the Iron Curtain and fueled research into antecedents and consequences of social cohesion. Currently extensions of the research program to the local level in Germany as well as to other regions of the world are discussed, and so are future assessments of social cohesion based on newly gathered data. Several contributions from the Bertelsmann project will form the backbone of the suggested session, but both a critical view at the concepts and analytic strategies of the research published so far as well as independent contributions to social indicator research in the sphere of social cohesion will be highly beneficial for the session.


Measurement errors in the wealth surveys 2 (O-201)

Convenor Mr Junyi Zhu (Deutsche Bundesbank)
Coordinator 1John Sabelhaus (Federal Reserve Board)
Coordinator 2Brian Bucks (Consumer Financial Protection Bureau)

Obtaining a comprehensive picture of households’ balance sheets and understanding their wealth accumulation process is of increasing interest to a large audience ranging from poli-cymakers and researchers to the general public. Consequently, more and more wealth surveys have been established worldwide. However, wealth data are susceptible to measurement errors specific to the nature of various asset and liability items. For example, households may not assess the value and amount of their assets constantly. And the valuation of less traded or distinctive assets is not straightforward. The knowledge required to answer some question can be demanding. Financial topics are always sensitive. Typically, questions on ownership of assets or liabilities are answered more accurately than questions on their value and in most cases the reporting quality of the debts outperforms that of the assets. Households from both ends of the wealth distribution are hard to identify and reach. The longitudinal data adds another layer of difficulty in distinguishing true changes from measurement errors. On the other hand, reporting error, the main measurement error, does not have a homogeneous pattern but can be classified.
We would like to invite survey practitioners to discuss how to detect and tackle measurement errors in wealth surveys. Researchers can analyze the missing pattern within the survey as a signal of potential errors. Matching to external surveys or administrative data and utilizing the panel dimension are other options to gauge the plausibility of answers. But then, there have been many prevention and reconciling measures. They include careful design and sequencing of questions, specialized interviewer training, software real-time checks, editing by reviewing the comments, dependent interviewing, etc. Innovative approaches are especially welcome. For example, using tax records, property lien data, online finance websites or other sources can fill the gap in building comprehensive profile of wealth accumulation.


Methods for Improving Causal Inference in the Social Sciences (HT-101)

Convenor Professor Jochen Mayerl (University of Kaiserslautern, Germany)
Coordinator 1Professor Volker Stocké (University of Kassel, GErmany)
Coordinator 2Professor Levente Littvay (Central European University, Hungary)

The central aim of social sciences is to discover the causal effect of explanatory variables on various outcomes. However, we are often restricted to quasi-experimental, observational and in particular cross sectional survey data. Under these conditions, the causal status of observed associations remains unclear, because of unobserved heterogeneity and reverse causation. At present the methodological tools for improving causal inference are not common knowledge.
These tools are firstly different kinds of fixed-effects estimation (e.g. school fixed-effects) which eliminates the possibly endogenous between-variance. When longitudinal panel data is available, different methods like individual fixed effects panel regression, cross-lagged autoregressive models, latent growth curve models, and autoregressive latent trajectory models are used to decide on causality. Differences-in-differences estimators can be used on the aggregate level. Secondly, matching-techniques (e.g. propensity score matching) comparing the difference of similar members of the treatment and control group are feasible as well. Thirdly, instrumental variable approaches, utilizing exogenous determinants of the treatment condition to estimate causal effects. Fourthly, regression discontinuity techniques are used in order to exploit variance at the edge between strata of the explanatory variables.
All these methods of causal analysis make certain assumptions, for instance no systematic missing data, the SUTVA-condition and unconfoundedness. In contrast to more common methods of analysis, the consequences of violations of these assumptions are much less analyzed. The same is true for decisions which have to be made when causal analyses are applied. For instance, which criterion should be used in the case of matching-techniques? How to judge the exogeneity and strength of an instrumental variable?

This session invites methodological and empirical contributions which apply methods for improving causal inference in survey research, compares them to “naive” methods or presents progress in methodological issues.


Mobile and mixed-device surveys (HT-105)

Convenor Dr Vera Toepoel (Utrecht University)
Coordinator 1Mrs Marika De Bruijne (CentERdata)
Coordinator 2Mr Arnaud Wijnant (CentERdata)

Mobile and mixed-device surveys

Online surveys can nowadays be completed on many devices. The devices range from a traditional desktop computer, to a tablet, smartphone or hybrids of these. There is a clear increase in the use of mobile devices for survey completion. Small displays and alternative input mechanisms impose challenges for survey research. In addition, the mixes of devices poses challenges to survey methodologists, mainly in questionnaire design and measurement error, but also in sampling and nonresponse conversion.

We are seeking presentations that highlight potential opportunities and problems in mobile and mixed-device data collection, compare different approaches to deal with these problems, and/or propose solutions. For example:

- how can mixed-devices help to reduce noncoverage and nonresponse bias?
- can survey respondents be effectively nudged towards using a particular device within a web-survey?
- what possibilities and threats do mixed-device survey open up for measurement?
- how to design Web survey questionnaires effectively for use across mobile or mixed-devices?
-etc.


Modelling unit nonresponse and attrition processes 2 (HT-102)

Convenor Ms Carina Cornesse (GIP, Mannheim University)
Coordinator 1Dr Gabriele Durrant (School of Social Sciences, University of Southampton)
Coordinator 2Professor Annelies Blom (GIP, Mannheim University)

This session focuses on analysing the processes leading to unit nonresponse in cross-sectional and attrition in longitudinal data. Unit nonresponse and attrition are major issues affecting data quality in surveys. Their importance has increased over the past decades as response rates in the US and Europe have been decreasing across survey modes and nonresponse rates may be related to nonresponse bias.

When modelling the fieldwork processes leading to nonresponse, research can draw on auxiliary data sources. These may include paradata, such as call record data, interviewer observations, time stamps during the interview, or variables from external data sources, such as administrative, register and census data.

In recent years, the statistical techniques that have been developed to model unit nonresponse and attrition and applied to survey data have become increasingly sophisticated. In addition, both ex-post modelling to learn from previous fieldwork outcomes and real-time modelling to inform adaptive and responsive survey designs have found its way into the survey methodological realm.

For our session we invite submissions from researchers who model unit nonresponse and attrition processes. We specifically encourage submissions of papers that use auxiliary data to model unit nonresponse and attrition processes and papers that use complex statistical models for this purpose.


Natural Experiments in Survey Research (L-102)

Convenor Professor Henning Best (University of Wuerzburg)
Coordinator 1Dr Gerrit Bauer (University of Munich )

In this session we are particularly interested in papers on identification of treatment effects in natural experiments, research combining surveys with natural-experimental designs, papers that employ multiple methods of treatment estimation, and innovative ways to design or analyze natural experiments in cross-sectional and especially panel surveys.

Though experiments are generally regarded as the royal road to causal inference, natural experiments often face serious problems: endogeneity, insufficiencies in standardizing treatment- and control conditions, and self-selection into study- and control group. Advances in data analysis have tackled these problems, and methods such as IV-regression, conditional fixed-effects models and propensity score matching help in identifying unbiased treatment effects.

We are not only interested in applications of natural experiments in the social sciences but especially encourage submissions on methods and designs. Examples of such methods include applications of IV-regression, conditional fixed-effects models, propensity score matching and regression discontinuity designs.


Social Desirability and Non-Reactive Methods in Survey Research: Improving Theory and Data Collection 1 (O-101)

Convenor Dr Ivar Krumpal (University of Leipzig)
Coordinator 1Professor Roger Berger (University of Leipzig)
Coordinator 2Professor Mark Trappmann (IAB Nürnberg)

Social desirability bias is a problem in surveys collecting data on private or norm-violating issues (e.g. sexual behavior, health related issues, voting preferences, income, or unsocial opinions) as soon as the respondent’s true score differs from his or her perception of the social desirable score. Due to the respondents’ strive for social approval and keeping a favourable self-image as well as data protection concerns, collecting valid data on private or norm-violating issues is a challenging task. More specifically, respondents may engage in impression management or self-deception or edit their answer before reporting it. Non-reactive data collection methods could improve measurements and data quality in surveys where social desirability bias is a potential problem. Therefore, the possibilities and limits of non-reactive methods (e.g. record linkage approaches, surveys without questions, biomarkers, field experiments or administrative data usage) will be critically discussed and compared to methods which are based on self-reports.

This session has four main goals: (1) discussion of the theoretical foundation of the research on social desirability bias in the context of a general theory of human psychology and social behavior. A clearer understanding of the social interactions between the actors that are involved in the data collection process could provide empirical researchers with a substantiated basis for optimizing their survey design and data collection to achieve high quality data; (2) presentation of current empirical research focusing on non-reactive methods of data collection in connection with the problem of social desirability; (3) discussion of new designs combining or contrasting non-reactive methods with standard ‘question-and-answer’ survey measurement in innovative ways; (4) exploration of possibilities of integrating such new and innovative approaches in well-established, large-scale population surveys taking into account problems of research ethics and data protection.


Student Involvement in Surveys (O-206)

Convenor Professor Mary Gray (American University, Washington DC)
Coordinator 1Mr Emmanuel Addo (American University, Washington DC)

Session proposal: Student Involvement in Surveys

There are many ways to include undergraduate and graduate students in survey classes in practical applications of what they are studying. Hearing of successful projects would assist and encourage other academics to involve their students at an early stage of their careers and would provide practical benefits to the students. Such projects also have been found to entice students in substantive fields of survey research to continue and expand their statistical training. Hands-on work that produces tangible results can be inspirational for young people as well as intrinsically valuable, especially when important policy issues are addressed. Such training can be organized not only through colleges and universities but also through groups such as Statisticians without Borders which provides pro bono assistance to NGOs, particularly in the developing world, in a framework that pairs experienced volunteers with novices. A session where examples of such projects are presented will open up broad possibilities for the development of participatory training to conference participants. For example, an exit poll survey in various states within the United States in November 2014 will examine the disparate effect on minority ethnic groups and rural, inner city and low income populations of voter ID laws that suppress access to the polls would be one potential contribution to the session; a successful pilot project in the state of Virginia is the model for this endeavor.


Substantive Analyses of Intensive Longitudinal Data (L-101)

Convenor Professor Jennifer Barber (University of Michigan)

Recent, rapid improvements in technology have greatly facilitated survey researchers' ability to collect frequent, closely-spaced surveys. This is sometimes called intensive longitudinal data, or frequent assessment panel data. Truly illuminating analyses of the resulting data , which take full advantage of the frequent assessments, can be challenging.

Some traditional analytic methods, such as hazard models and linear growth curve models, are well-suited to intensive longitudinal data because they involve time-varying variables, and the intensive longitudinal data are easily translated into such time-varying variables. However, standard latent trajectory methods have difficulty with 100+ assessments per unit of analysis. In addition, intensive longitudinal data are particularly well-suited for examining transitions, sequences, and patterns, which are not easily illustrated with traditional analytic methods.

This session will present examples of innovative substantive research using many closely spaced assessments per unit of analysis. These examples will spur other researchers to analyze their own intensive longitudinal data in new and innovative ways.


Survey Research in Developing Countries 2 (L-103)

Convenor Dr Irene Pavesi (Small Arms Survey)

This session explores the challenges involved in conducting survey research in developing countries and discuss best practices in sampling, questionnaire design and fieldwork organisation.

Even more often than in developed countries up-to-date data on population size and composition is absent. Mobile populations, scarcely populated areas and areas connected only by low quality roads and security issues complicate the creation of a sampling frame. What strategies have researchers used to deal with these challenges?

Response rates tend to be high in developing countries. This is in part because in rural areas trust tends to be high or a survey is seen as an interesting break from everyday life. However in some cases the consent of village heads or other local leaders is an order to people to participate. How does this fit with the idea of informed consent?

High poverty in some areas raises ethical questions on whether and how respondents should be compensated for their time; if respondents receive cash or in kind compensation this can lead to competition among households for inclusion in the survey. What are appropriate ways to compensate respondents?

Large household with complex structures can make collection of household data a time consuming and error prone process. How can data be collected in an efficient way?

High ethnic and linguistic diversity poses challenges to both questionnaire translation and selection of interviewers. How can these challenges be dealt with?

If the people who design the questionnaire are not from the country of data collection, what procedures can be used to ensure that concepts in the survey resonate with those of the target population?

We welcome papers on these and related topics, such as reaching female respondents, use of ICT in data collection, surveying in (post-)conflict areas, and surveys among populations with high illiteracy rates


The impact of questionnaire design on measurements in surveys 3 (HT-104)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Ms Kathrin Bogner (GESIS)

Questionnaire design is crucial for obtaining high-quality survey data. Still, there is a great need for research that helps to better understand how and under which conditions different design aspects of questionnaires impact measurement process and survey data quality. Therefore, researchers are invited to submit papers dealing with questionnaire design features such as question wording, visual design and answer formats, instructions, introductions and other relevant design aspects of questionnaires. Also, different means of measurement such as questions with nominal answer categories, rankings, ratings, sematic differentials or vignettes can be addressed or can be matter of comparison. Of interest is the impact of questionnaire design on response behavior, on systematic as well as non-systematic error or on validity. In addition, respondents’ cognition or motivation can be in focus of the studies.


Uses of Geographic Information Systems Tools in Survey Data Collection & Analysis (HT-103)

Convenor Dr Stephanie Eckman (IAB)
Coordinator 1Mr Ned English (NORC)

The application of Geographic Information Systems (GIS) and related tools to survey data collection and analysis has dramatically increased in recent years. Traditionally, GIS tools have been applied primarily in the frame construction, sampling, and data collection phases of survey research. More recently, researchers have begun to use records of interviewer travel to detect falsification and determine how to make data collection more efficient. The techniques of geostatistics and geospatial models can provide new methods for studying and reducing nonresponse and measurement error. As these technologies become less expensive and easier to use, and geographic data becomes more widely available on the web, we expect survey researchers to find even more uses for these tools. While we embrace these tools, however, we should also maintain a healthy skepticism about their capabilities and limitations.

This series of sessions at the ESRA 2015 conference will bring together survey researchers from different countries to discuss novel applications of GIS technology to data collection and analysis and to share ideas. We encourage papers that discuss the use GIS or GPS technologies in any stage of the survey process, and how these tools can help us understand, reduce or adjust for different error sources. We are also interested in papers that review errors in GIS technology and how they can impact survey quality.


Values and Value Change in a Changing World 1 (N-132)

Convenor Dr Malina Voicu (GESIS Leibniz Institute for the Social Sciences)
Coordinator 1Dr Hermann Dülmer (University of Cologne)

Values are socialized during formative years and deeply rooted in individual personality. However, people do not always strictly follow their value priorities acquired during early socialization and do not ignore changing in their living environment. Ronald Inglehart assumed that economic and physical security during one’s formative years has an important influence on his /her value orientation (socialization hypothesis). On the other hand, values may also adapt to changes in environment (scarcity hypothesis). People who grown up in affluent societies become more tolerant towards minorities or with respect to family norms and sexuality and are more interested and more engaged in politics. What are the long term consequences on values of decreasing affluence due to the economic crisis experienced by many European countries during last years? Do people become less tolerant and less politically engaged? What is the impact of changing in living conditions on different values like universalism, conformity, or security as distinguished by Shalom Schwartz? Does changing in living conditions impact in the same way on values’ structure distinguished by Inglehart and Schwartz? Can similarities and differences be identified?

This session welcomes contributions that try to investigate empirically the impact of changing environment conditions on values and attitudes. We particularly encourage submissions based on international comparisons, using comparative survey data such as European Values Study, World Values Survey, European Social Survey, or International Social Survey Program. Substantive contributions, approaching the impact of changing in living conditions on values as well as innovative methodological approaches, which, by instance, help disentangling age, cohort and period effects, are equally welcomed.


Analysis of Cognitive Interview Data 1 (O-206)

Convenor Dr Kristen Miller (National Center for Health Statistics)
Coordinator 1Kristen Miller
Coordinator 2Gordon Willis (National Cancer Institute)

While researchers have analyzed cognitive interviews in a variety of ways, there has been little discussion regarding the process of analysis in cognitive interview literature. That is, there has been little explanation as to how cognitive interviews should be examined and studied to produce reputable findings. In the past year, however, this void has begun to be addressed by publications presenting various analytic techniques for producing cognitive interview findings. Additionally, it has just recently been recognized that cognitive interviewing studies can serve multiple functions toward understanding the performance of a survey question. As traditionally understood, cognitive interviewing studies can identify various difficulties that respondents may experience when attempting to answer a survey question. Cognitive interviewing studies may also examine construct validity in that they can identify the content or experiences that respondents consider and ultimately include in their answer. Finally, cognitive interviewing studies can examine issues of comparability, for example, the accuracy of translations or equivalence across socio-cultural groups. The type of analytic processes employed within a cognitive interviewing study guides the types of conclusions that can be made. This session will focus specifically on issues related to the analysis of cognitive interviews. Topics include analytic techniques, specific methods for addressing study goals (e.g. accuracy of translations and cross-cultural comparability), practices to support study transparency and believability, and ways of assessing and addressing varying levels of data quality,


Assessing and addressing measurement equivalence in cross-cultural surveys 1 (O-101)

Convenor Dr Gijs Van Houten (Eurofound)
Coordinator 1Dr Milos Kankaras (Eurofound)

Over the past decades the number of cross-cultural surveys has increased dramatically. A major challenge in cross-cultural surveys is to ensure that the answers of different respondents to survey items measure the same concepts. If measurement equivalence is not achieved it is difficult if not impossible to make meaningful comparisons across cultures and countries.

Most cross-cultural surveys aim to reduce bias by finding the right balance between harmonisation and local adaptation of the methods used in each of the stages of the surveys process (e.g. sampling, questionnaire development and translation, fieldwork implementation etc.). Furthermore, an increasing number of research projects are being carried out looking into the determinants measurement equivalence. There are three main approaches to the analysis of measurement equivalence – multigroup confirmatory factor analysis, differential item functioning, and multigroup latent class analysis. These latent variable models are based on different modelling assumptions and are appropriate for different types of data (cf. Kankaraš and Moors, 2010).

This session invites papers about the assessment of measurement equivalence in cross-cultural surveys as well as papers about efforts made to address measurement equivalence in the design and implementation of surveys. The aim is to facilitate an exchange that benefits both the future analysis of measurement equivalence and the future design of cross-national surveys.

Kankaraš, M. & Moors, G.B.D (2010). Researching measurement equivalence in cross-cultural studies. Psyhologija, 43(2) ,121-136


Linking survey data and auxiliary data sources: statistical aspects and substantive applications 1 (HT-103)

Convenor Ms Chiara Peroni (STATEC)
Coordinator 1Mr Francesco Sarracino (STATEC, HSE-LCSR)
Coordinator 2Mr Wladimir Raymond (STATEC)

This session aims to collect contributions from applied research linking survey data with auxiliary data sources. This involves merging various surveys or using information from data collected at different levels, such as macro and individual-level data, administrative data, and other surveys, possibly including those from mobile devices. This permits to address complex research questions, while avoiding the need of long surveys which are costly to run, respond and administer. This strategy, however, poses various methodological challenges concerning the weighting procedure, the computation of standard errors, and the imputation of missing data. These challenges have to be correctly identified and addressed to reach methodologically sound conclusions. We welcome applications to the following topics:

• innovation & social mobility;
• entrepreneurship;
• job and life satisfaction and economic performance;
• migration;

as well as those dealing with methodological issues such as weighting schemes, imputation of missing data and computation of standard errors.


Longitudinal surveys - challenges in running panel studies 1 (O-202)

Convenor Dr Jutta Von Maurice (Leibniz Institute for Educational Trajectoires)
Coordinator 1Ms Joanne Corey (Australian Bureau of Statistics)

Longitudinal surveys - challenges in running panel studies.

This session will focus on the organisation of panel studies, including panel maintenance, panel engagement, sample review processes, choice of data items and methodologies, and interviewer training.

The focus is on the particular challenges faced by those running panel studies such as:

. maintaining up-to-date contact information and tracking of respondents, including privacy concerns;

. engaging repsondents over the life of the survey, particularly for different age groups, for example how to keep young people interested as they move from children to young adults and they become the primary consenter;

. how successful are different modes for making contact, e.g. mail, phone, text;

. do targeted approach stategies work, e.g. different approach letters depending on past wave response;

. decision making guidelines about when a respondent should be removed from the sample;

. the debate between longitudinal consistency and using a better/updated measure;

. how to conduct training for a mix of experienced and new interviewers, balanced with the amount of new content and methodologies; and

.testing techniques for longitudinal surveys.


Measurement errors in the wealth surveys 3 (O-201)

Convenor Mr Junyi Zhu (Deutsche Bundesbank)
Coordinator 1John Sabelhaus (Federal Reserve Board)
Coordinator 2Brian Bucks (Consumer Financial Protection Bureau)

Obtaining a comprehensive picture of households’ balance sheets and understanding their wealth accumulation process is of increasing interest to a large audience ranging from poli-cymakers and researchers to the general public. Consequently, more and more wealth surveys have been established worldwide. However, wealth data are susceptible to measurement errors specific to the nature of various asset and liability items. For example, households may not assess the value and amount of their assets constantly. And the valuation of less traded or distinctive assets is not straightforward. The knowledge required to answer some question can be demanding. Financial topics are always sensitive. Typically, questions on ownership of assets or liabilities are answered more accurately than questions on their value and in most cases the reporting quality of the debts outperforms that of the assets. Households from both ends of the wealth distribution are hard to identify and reach. The longitudinal data adds another layer of difficulty in distinguishing true changes from measurement errors. On the other hand, reporting error, the main measurement error, does not have a homogeneous pattern but can be classified.
We would like to invite survey practitioners to discuss how to detect and tackle measurement errors in wealth surveys. Researchers can analyze the missing pattern within the survey as a signal of potential errors. Matching to external surveys or administrative data and utilizing the panel dimension are other options to gauge the plausibility of answers. But then, there have been many prevention and reconciling measures. They include careful design and sequencing of questions, specialized interviewer training, software real-time checks, editing by reviewing the comments, dependent interviewing, etc. Innovative approaches are especially welcome. For example, using tax records, property lien data, online finance websites or other sources can fill the gap in building comprehensive profile of wealth accumulation.


Measuring social relations, social networks and social capital in comparative surveys 1 (N-131)

Convenor Mr Christof Wolf (GESIS - Leibniz-Institute for the Social Sciences)
Coordinator 1Mr Dominique Joye (University Lausanne)

The measurement of social relations, social networks and social capital, here understood as resources accessible through one’s social relations, has attracted a lot of attention. Dependent on the intended purpose there exists instruments to measure aspects of specific relations (spouse, best friend), instrument capturing “personal communities”, i.e. the egocentric network approach, or instruments measuring social capital through, for example, social support questionnaires or the position or resource generators.

While we know a lot about the performance of these measures in a national context we lack information on their performance in comparative studies. This session therefore aims to explore the challenges posed by adapting survey instruments measuring social relations, social networks and social capital to a comparative, cross-national investigation. These challenges include problems of
• equivalence of the meaning of stimuli; e.g. do the terms “friends”, “discuss important matters” or “to be close to someone” have the same meaning across countries.
• equivalence of resources; e.g. is knowing a person who can lend me money or who can repair my car equally important in all societies? or
• equivalence of occupations selected for the position generator; e.g. can we find a set of occupations that reflects the entire social structure of different countries equally well?

Of course, these are only few selected examples and there exists many more. We welcome all contributions investigating the challenges encountered when trying to measure social relations, network and capital in cross-national surveys


Multifactorial Survey Experiments (Factorial Surveys, Choice Experiments and Conjoint Analysis) 1 (L-102)

Convenor Professor Katrin Auspurg (Goethe-University Frankfurt)
Coordinator 1Dr Carsten Sauer (Bielefeld University)
Coordinator 2Professor Peter M. Steiner (University of Wisconsin-Madison)

There is a fast growing trend in the social sciences to combine the advantages of multifactorial experimental designs with surveys. Factorial surveys – often labelled as “vignettes studies” – have been used for more than 30 years to gather data on descriptions of hypothetical situations or objects to explore principles of judgment and decision making. Choice experiments help to explore respondents’ preferences and willingness to pay. In addition there is increasing use of conjoint analyses in sociology and political sciences. The experimental design provides a high internal validity, while the survey design improves external validity. Computer assisted interviewing that allows implementing many different treatments have made these methods even more popular.

Despite frequent use there are still many open questions concerning design features of multifactorial survey experiments that offer most reliable and valid results. We are interested in methodological research on the design of factorial surveys, choice experiments or conjoint analyses (e.g., validity of tabular vs. text presentations, video-vignettes), sampling techniques to select the experimental treatments (random sampling vs. fractional sampling), analysis strategies (e.g. accounting for the multi-level structure of response data; testing validity in regard to respondents’ attitudes, beliefs, and behavior).


Questions could be:
Design of questionnaire: How to present the vignettes to the respondents? What kind of answering scale provides most valid results? How to prevent order effects? How do respondents cope with the information provided on vignettes or choice sets?
Sampling techniques: What are the benefits and drawbacks of fractional versus random sampling? How do sampling techniques like blocking by respondent strata and interviewers influence efficiency of estimates?
Analysis strategies and validity: Which models provide unbiased estimates? How to address possible censoring of responses? Respondents’ idiosyncracies? When to use multilevel analyses, and how to validate results?


Push2Web and Nudge2Web: Combining Mail and Online Survey Modes to Reduce Survey Errors and Survey Cost (HT-105)

Convenor Professor Henning Best (University of Wuerzburg)
Coordinator 1Professor Michael Bosnjak (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 2Mrs Tanja Dannwolf (GESIS - Leibniz Institute for the Social Sciences)

The sharp decline in telephone survey response rates has strongly increased the need for alternative ways for surveying the general public. Web surveys with offline recruiting are a potentially promising option, but at the moment internet use and coverage is still limited. As a possible solution to this problem, Dillman and Colleagues have recently suggested using a sequential mixed-mode design combining mail and web survey modes (see e.g. Messer & Dillman 2011). The key idea is to initially contacting the respondents by mail, ´pushing´ them to the web mode (Push2Web) and finally providing a paper questionnaire as a last resort to avoid unit nonresponse. The type of mode the respondents are expected to participate in is under the control of the researcher. Another conceivable strategy is to leave the mode choice to the respondents, and using various strategies ´nudging´ them to the web mode (Nudge2Web).

While these approaches appear promising, important questions on survey errors and biases (coverage, sampling, nonresponse, measurement) and survey costs, as well as questions of practical survey management remain understudied.

This session is aimed at bringing together pertinent research and recent experiences on combining offline recruitment and mixed-mode (especially mail+web) surveys from Europe, and encourages submissions about the impact of various Push2Web or Nudge2Web strategies on survey errors and costs.


Recent developments in survey metadata capture, discovery and harmonisation (O-106)

Convenor Ms Louise Corti (UK Data Archive, University of Essex)
Coordinator 1Jon Johnson (Centre for Longitudinal Studies, Institute of Education)
Coordinator 2Joachim Wackerow (GESIS)

There are increasing numbers of survey metadata search and browse tools available on the web. These tools – question banks, variable searches and the like – are in various states of maturity, adhere to a variety of standards (and none) and provide access to a range of survey metadata. Despite their differences, a key thread running through all of these tools is the need to capture metadata as early on in the survey life-cycle as possible. Not only does this aid survey data management during data collection, it is also crucial to the storage and retrieval of metadata required for accurate and efficient archiving; itself, a pre-requisite for successful resource discovery later on, especially where metadata items are re-used (for example, in continuing survey series or longitudinal studies).

Current versions of CAI software are, however, limited in their ability to provide this metadata, even as a by-product of their primary function of collecting data. This session will address the cultural, logistical and technical barriers to the contemporaneous capture of these metadata. It will also showcase emerging solutions to the problem, including developments in the extraction of survey metadata from CAI scripts to create XML files compliant with metadata standards such as the Data Documentation Initiative (DDI).

The adoption by fieldwork agencies of metadata standards such as DDI is also dependent upon a critical mass of existing survey metadata upon which to draw. This session will also address recent developments in the UK and elsewhere in Europe where the creation of historical survey metadata repositories could be used to inform the future collection of metadata not only for discovery purposes but also to flag harmonisations and equivalences across surveys/studies.


Recent developments in the analysis of panel data 2 (L-101)

Convenor Dr Klaus Pforr (GESIS – Leibniz-Institute for the Social Sciences)
Coordinator 1Professor Josef Brüderl (Department of Sociology, University of Munich)
Coordinator 2Dr Jette Schröder (GESIS – Leibniz-Institute for the Social Sciences)

Panel data offer two major advantages compared to cross-sectional data:
1) They allow to identify causal effects under weaker assumptions (within estimation)
2) They allow to estimate individual trajectories over time (growth curve modeling)
Not all model classes that are available for panel data analysis, exploit these advantages fully.
There is much uncertainty amongst users, which kind of models to use. On the other side, there
are new model classes, for which it is quite unclear what the assumptions are that they need to
identify a causal effect (e.g. structural equation models for panel data, and multi-level models).
Therefore, we especially welcome papers that
1) compare different model classes and their usefulness for panel data analyses, or that
2) apply recently developed model classes and explicate their assumptions.


Survey Research in Developing Countries 3 (L-103)

Convenor Dr Irene Pavesi (Small Arms Survey)

This session explores the challenges involved in conducting survey research in developing countries and discuss best practices in sampling, questionnaire design and fieldwork organisation.

Even more often than in developed countries up-to-date data on population size and composition is absent. Mobile populations, scarcely populated areas and areas connected only by low quality roads and security issues complicate the creation of a sampling frame. What strategies have researchers used to deal with these challenges?

Response rates tend to be high in developing countries. This is in part because in rural areas trust tends to be high or a survey is seen as an interesting break from everyday life. However in some cases the consent of village heads or other local leaders is an order to people to participate. How does this fit with the idea of informed consent?

High poverty in some areas raises ethical questions on whether and how respondents should be compensated for their time; if respondents receive cash or in kind compensation this can lead to competition among households for inclusion in the survey. What are appropriate ways to compensate respondents?

Large household with complex structures can make collection of household data a time consuming and error prone process. How can data be collected in an efficient way?

High ethnic and linguistic diversity poses challenges to both questionnaire translation and selection of interviewers. How can these challenges be dealt with?

If the people who design the questionnaire are not from the country of data collection, what procedures can be used to ensure that concepts in the survey resonate with those of the target population?

We welcome papers on these and related topics, such as reaching female respondents, use of ICT in data collection, surveying in (post-)conflict areas, and surveys among populations with high illiteracy rates


The impact of questionnaire design on measurements in surveys 4 (HT-104)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Ms Kathrin Bogner (GESIS)

Questionnaire design is crucial for obtaining high-quality survey data. Still, there is a great need for research that helps to better understand how and under which conditions different design aspects of questionnaires impact measurement process and survey data quality. Therefore, researchers are invited to submit papers dealing with questionnaire design features such as question wording, visual design and answer formats, instructions, introductions and other relevant design aspects of questionnaires. Also, different means of measurement such as questions with nominal answer categories, rankings, ratings, sematic differentials or vignettes can be addressed or can be matter of comparison. Of interest is the impact of questionnaire design on response behavior, on systematic as well as non-systematic error or on validity. In addition, respondents’ cognition or motivation can be in focus of the studies.


Unit and item nonresponse 2 (HT-102)

Convenor Mr Peter Linde (Statistics Denmark)

Greater response for less money
Quality improvements frequently result in increased costs, e.g. in order to reduce nonresponse. However, nonresponse does not only depend on the number of attempts at making contact and mode, but also on the actual and experienced burden. Consequently, increased focus on reducing the experienced burden can be instrumental in increasing the achievement. The theme is discussed by examples from Statistics Denmark, where new digital solutions, better letters, prizes, reminders as to agreements, follow-up and interview training resulted in a higher degree of achievement as well as lower total costs. Concrete 6% less nonresponse and 10% less interview cost.


Using Survey Data for Spatial Analysis 1 (HT-101)

Convenor Professor Nina Baur (Technische Universität Berlin)
Coordinator 1Ms Linda Hering (Technische Universität Berlin)
Coordinator 2Ms Cornelia Thierbach (Technische Universität Berlin)

The session aims at exploring new developments in spatial methids, seeing space either as dependent or independent variable: Researchers can ask how people think about space and construct space or they can see space as a relevant frame for social action that influences social life. Papers address one of the questions below either at a more general methodological level or using a concrete example in a specific research project:

(1) How can survey data be used for spatial analysis? Can they be used by themselves, or do they have to be mixed with other data, e.g. geodata, qualitative data?

(2) What methodological innovations concerning the spatial can be observed? (How) can traditional sociological or geographical methods be adjusted to address spatial problems within sociology?

(3) Which sampling strategies are appropriate for spatial problems?

(4) Which strategies of data analysis are appropriate for spatial analysis?


Values and Value Change in a Changing World 2 (N-132)

Convenor Dr Malina Voicu (GESIS Leibniz Institute for the Social Sciences)
Coordinator 1Dr Hermann Dülmer (University of Cologne)

Values are socialized during formative years and deeply rooted in individual personality. However, people do not always strictly follow their value priorities acquired during early socialization and do not ignore changing in their living environment. Ronald Inglehart assumed that economic and physical security during one’s formative years has an important influence on his /her value orientation (socialization hypothesis). On the other hand, values may also adapt to changes in environment (scarcity hypothesis). People who grown up in affluent societies become more tolerant towards minorities or with respect to family norms and sexuality and are more interested and more engaged in politics. What are the long term consequences on values of decreasing affluence due to the economic crisis experienced by many European countries during last years? Do people become less tolerant and less politically engaged? What is the impact of changing in living conditions on different values like universalism, conformity, or security as distinguished by Shalom Schwartz? Does changing in living conditions impact in the same way on values’ structure distinguished by Inglehart and Schwartz? Can similarities and differences be identified?

This session welcomes contributions that try to investigate empirically the impact of changing environment conditions on values and attitudes. We particularly encourage submissions based on international comparisons, using comparative survey data such as European Values Study, World Values Survey, European Social Survey, or International Social Survey Program. Substantive contributions, approaching the impact of changing in living conditions on values as well as innovative methodological approaches, which, by instance, help disentangling age, cohort and period effects, are equally welcomed.


Advancements of survey design in election polls and surveys 1 (N-132)

Convenor Ms Vilma Agalioti-sgompou (ISER University of Essex)

Political attitudes and behaviour are the main objects of measurement of Polls and Election Surveys. However, as it happens with surveys, they are affected from different types of error; for example, coverage error, questionnaire design effects, mode effects. Measurement error in political polls and election surveys can create different results between surveys. A distinct challenge for the researchers that aim at predicting electoral behaviour is that the reliability of the survey measurement is ‘tested’ with real electoral outcomes. This provides a unique opportunity for the validation of survey findings and examination of survey research quality.
The aim of this session is to provide a space for the latest advances in the design and development of polls and election surveys.

We welcome papers that investigate any methodological aspect of polls or surveys that:
a) measure political behaviour and/or attitudes, and,
b) provide validated information through administrative data or election outcomes.


Analysis of Cognitive Interview Data 2 (O-206)

Convenor Dr Kristen Miller (National Center for Health Statistics)
Coordinator 1Kristen Miller
Coordinator 2Gordon Willis (National Cancer Institute)

While researchers have analyzed cognitive interviews in a variety of ways, there has been little discussion regarding the process of analysis in cognitive interview literature. That is, there has been little explanation as to how cognitive interviews should be examined and studied to produce reputable findings. In the past year, however, this void has begun to be addressed by publications presenting various analytic techniques for producing cognitive interview findings. Additionally, it has just recently been recognized that cognitive interviewing studies can serve multiple functions toward understanding the performance of a survey question. As traditionally understood, cognitive interviewing studies can identify various difficulties that respondents may experience when attempting to answer a survey question. Cognitive interviewing studies may also examine construct validity in that they can identify the content or experiences that respondents consider and ultimately include in their answer. Finally, cognitive interviewing studies can examine issues of comparability, for example, the accuracy of translations or equivalence across socio-cultural groups. The type of analytic processes employed within a cognitive interviewing study guides the types of conclusions that can be made. This session will focus specifically on issues related to the analysis of cognitive interviews. Topics include analytic techniques, specific methods for addressing study goals (e.g. accuracy of translations and cross-cultural comparability), practices to support study transparency and believability, and ways of assessing and addressing varying levels of data quality,


Assessing and addressing measurement equivalence in cross-cultural surveys 2 (O-101)

Convenor Dr Gijs Van Houten (Eurofound)
Coordinator 1Dr Milos Kankaras (Eurofound)

Over the past decades the number of cross-cultural surveys has increased dramatically. A major challenge in cross-cultural surveys is to ensure that the answers of different respondents to survey items measure the same concepts. If measurement equivalence is not achieved it is difficult if not impossible to make meaningful comparisons across cultures and countries.

Most cross-cultural surveys aim to reduce bias by finding the right balance between harmonisation and local adaptation of the methods used in each of the stages of the surveys process (e.g. sampling, questionnaire development and translation, fieldwork implementation etc.). Furthermore, an increasing number of research projects are being carried out looking into the determinants measurement equivalence. There are three main approaches to the analysis of measurement equivalence – multigroup confirmatory factor analysis, differential item functioning, and multigroup latent class analysis. These latent variable models are based on different modelling assumptions and are appropriate for different types of data (cf. Kankaraš and Moors, 2010).

This session invites papers about the assessment of measurement equivalence in cross-cultural surveys as well as papers about efforts made to address measurement equivalence in the design and implementation of surveys. The aim is to facilitate an exchange that benefits both the future analysis of measurement equivalence and the future design of cross-national surveys.

Kankaraš, M. & Moors, G.B.D (2010). Researching measurement equivalence in cross-cultural studies. Psyhologija, 43(2) ,121-136


Discussion and/or applications of SQP2.0 (O-201)

Convenor Professor Willem Saris (RECSM, UPF)
Coordinator 1Dr Melanie Revilla (RECSM, UPF)

Recently, the first organizer of this session and Daniel Oberski received the Warren J. Mitofsky Innovators Award for the Survey Quality Predictor SQP 2.0 and its contribution to the improving questionnaire design. Although we appreciate very much this award, we think that there is still a lot of work to be done so that this tool can really play the role we hope it can play in survey research with respect to design of questionnaires and to correct for measurement errors in survey analysis.
In order to go further with this work, we invite all interested people, who have studied the SQP approach and would like to comment on its design or have applied the program and like to share their experience with others, to provide an abstract of a paper about their work for our session at the ESRA conference 2015. Papers about all different steps that are required to achieve the SQP program are welcome: MTMM estimation, meta-analysis of quality estimates, program itself and applications to improve surveys or correct for measurement errors…


Linking survey data and auxiliary data sources: statistical aspects and substantive applications 2 (HT-103)

Convenor Ms Chiara Peroni (STATEC)
Coordinator 1Mr Francesco Sarracino (STATEC, HSE-LCSR)
Coordinator 2Mr Wladimir Raymond (STATEC)

This session aims to collect contributions from applied research linking survey data with auxiliary data sources. This involves merging various surveys or using information from data collected at different levels, such as macro and individual-level data, administrative data, and other surveys, possibly including those from mobile devices. This permits to address complex research questions, while avoiding the need of long surveys which are costly to run, respond and administer. This strategy, however, poses various methodological challenges concerning the weighting procedure, the computation of standard errors, and the imputation of missing data. These challenges have to be correctly identified and addressed to reach methodologically sound conclusions. We welcome applications to the following topics:

• innovation & social mobility;
• entrepreneurship;
• job and life satisfaction and economic performance;
• migration;

as well as those dealing with methodological issues such as weighting schemes, imputation of missing data and computation of standard errors.


Longitudinal surveys - challenges in running panel studies 2 (O-202)

Convenor Dr Jutta Von Maurice (Leibniz Institute for Educational Trajectoires)
Coordinator 1Ms Joanne Corey (Australian Bureau of Statistics)

Longitudinal surveys - challenges in running panel studies.

This session will focus on the organisation of panel studies, including panel maintenance, panel engagement, sample review processes, choice of data items and methodologies, and interviewer training.

The focus is on the particular challenges faced by those running panel studies such as:

. maintaining up-to-date contact information and tracking of respondents, including privacy concerns;

. engaging repsondents over the life of the survey, particularly for different age groups, for example how to keep young people interested as they move from children to young adults and they become the primary consenter;

. how successful are different modes for making contact, e.g. mail, phone, text;

. do targeted approach stategies work, e.g. different approach letters depending on past wave response;

. decision making guidelines about when a respondent should be removed from the sample;

. the debate between longitudinal consistency and using a better/updated measure;

. how to conduct training for a mix of experienced and new interviewers, balanced with the amount of new content and methodologies; and

.testing techniques for longitudinal surveys.


Measuring social relations, social networks and social capital in comparative surveys 2 (N-131)

Convenor Mr Christof Wolf (GESIS - Leibniz-Institute for the Social Sciences)
Coordinator 1Mr Dominique Joye (University Lausanne)

The measurement of social relations, social networks and social capital, here understood as resources accessible through one’s social relations, has attracted a lot of attention. Dependent on the intended purpose there exists instruments to measure aspects of specific relations (spouse, best friend), instrument capturing “personal communities”, i.e. the egocentric network approach, or instruments measuring social capital through, for example, social support questionnaires or the position or resource generators.

While we know a lot about the performance of these measures in a national context we lack information on their performance in comparative studies. This session therefore aims to explore the challenges posed by adapting survey instruments measuring social relations, social networks and social capital to a comparative, cross-national investigation. These challenges include problems of
• equivalence of the meaning of stimuli; e.g. do the terms “friends”, “discuss important matters” or “to be close to someone” have the same meaning across countries.
• equivalence of resources; e.g. is knowing a person who can lend me money or who can repair my car equally important in all societies? or
• equivalence of occupations selected for the position generator; e.g. can we find a set of occupations that reflects the entire social structure of different countries equally well?

Of course, these are only few selected examples and there exists many more. We welcome all contributions investigating the challenges encountered when trying to measure social relations, network and capital in cross-national surveys


Multifactorial Survey Experiments (Factorial Surveys, Choice Experiments and Conjoint Analysis) 2 (L-102)

Convenor Professor Katrin Auspurg (Goethe-University Frankfurt)
Coordinator 1Dr Carsten Sauer (Bielefeld University)
Coordinator 2Professor Peter M. Steiner (University of Wisconsin-Madison)

There is a fast growing trend in the social sciences to combine the advantages of multifactorial experimental designs with surveys. Factorial surveys – often labelled as “vignettes studies” – have been used for more than 30 years to gather data on descriptions of hypothetical situations or objects to explore principles of judgment and decision making. Choice experiments help to explore respondents’ preferences and willingness to pay. In addition there is increasing use of conjoint analyses in sociology and political sciences. The experimental design provides a high internal validity, while the survey design improves external validity. Computer assisted interviewing that allows implementing many different treatments have made these methods even more popular.

Despite frequent use there are still many open questions concerning design features of multifactorial survey experiments that offer most reliable and valid results. We are interested in methodological research on the design of factorial surveys, choice experiments or conjoint analyses (e.g., validity of tabular vs. text presentations, video-vignettes), sampling techniques to select the experimental treatments (random sampling vs. fractional sampling), analysis strategies (e.g. accounting for the multi-level structure of response data; testing validity in regard to respondents’ attitudes, beliefs, and behavior).


Questions could be:
Design of questionnaire: How to present the vignettes to the respondents? What kind of answering scale provides most valid results? How to prevent order effects? How do respondents cope with the information provided on vignettes or choice sets?
Sampling techniques: What are the benefits and drawbacks of fractional versus random sampling? How do sampling techniques like blocking by respondent strata and interviewers influence efficiency of estimates?
Analysis strategies and validity: Which models provide unbiased estimates? How to address possible censoring of responses? Respondents’ idiosyncracies? When to use multilevel analyses, and how to validate results?


Recent developments in the analysis of panel data 1 (L-101)

Convenor Dr Klaus Pforr (GESIS – Leibniz-Institute for the Social Sciences)
Coordinator 1Professor Josef Brüderl (Department of Sociology, University of Munich)
Coordinator 2Dr Jette Schröder (GESIS – Leibniz-Institute for the Social Sciences)

Panel data offer two major advantages compared to cross-sectional data:
1) They allow to identify causal effects under weaker assumptions (within estimation)
2) They allow to estimate individual trajectories over time (growth curve modeling)
Not all model classes that are available for panel data analysis, exploit these advantages fully.
There is much uncertainty amongst users, which kind of models to use. On the other side, there
are new model classes, for which it is quite unclear what the assumptions are that they need to
identify a causal effect (e.g. structural equation models for panel data, and multi-level models).
Therefore, we especially welcome papers that
1) compare different model classes and their usefulness for panel data analyses, or that
2) apply recently developed model classes and explicate their assumptions.


Structured Metadata: applications, processes, perspectives (O-106)

Convenor Mr Knut Wenzig (DIW Berlin / GSOEP)
Coordinator 1Mr Daniel Bela (LIfBi / NEPS)

Various metadata systems for different sections of the data management lifecycle (e.g. questionnaire development, data preparation, documentation, data dissemination) are in use at institutions dealing with survey research. Resulting benefits are manifold: Data users can take advantage of metadata driven portals which make it easy to search for variables; instrument developers can quickly find questions used in other surveys.

Some of these metadata systems make use of evolving metadata standards (such as DDI or SDMX), some others are developed independently as custom-tailored solutions. Most of them have one idea in common: Structured metadata, stored in relational databases, make it possible to have one single source of information for data on data.

While metadata infrastructure in the first instance sets up the framework, processes have to be established to deploy these systems. As this fact seems to be underexposed in the academic discussion, this session aims to focus on systems which are already implemented and in productive use.

Papers presented in the session should focus on the features of metadata systems, e.g. on the re-use of information on objects, the capability to deal with multilingual content or to drive data preparation, and their practical implementation.
We also want to promote transfer of knowledge about distinct (e.g. serial versus simultaneous) work-flows in using and implementing approaches of managing and making use of metadata.

Finally, this session gives the possibility to discuss the perspectives of different systems concerning deployment in other environments, interfaces to standards or lessons learned during software development.


Surveying children and young people 2 (L-103)

Convenor Miss Emily Gilbert (Centre for Longitudinal Studies, Institute of Education)
Coordinator 1Ms Lisa Calderwood (Centre for Longitudinal Studies, Institute of Education)

Many large-scale surveys successfully collect a variety of different types of data from children and young people. However, there is relatively little methodological evidence in this area. Much of the literature relating to children and young people’s participation in research focuses on small-scale qualitative studies and tends to concentrate on ethical issues relating to the rights of children and young people in research. This session will cover experiences of including children and young people in surveys, and related survey design issues. The session aims to explore a variety of methodological issues around surveying children and young people. Submissions are particularly welcomed on:
- designing questionnaires for children and young people, including question testing methods
- collecting sensitive data from children and young people, including methods for ensuring privacy and encouraging accurate reporting
- collecting different types of data from children and young people, including physical measurements, cognitive assessments, biological samples and time use data
- using different methods of data collection, including the use of innovative technology such as the web and mobile phones
- inclusivity in data collection methods, including facilitating the participation of young people with lower literacy levels
- assessing the reliability and validity of young people’s self-reports
- preventing non-response by engaging young people in research, including designing survey materials to appeal to young people and using new technology and digital media for participant engagement
- ethical issues in involving children and young people in surveys, including gaining informed consent and protecting children’s rights and well-being


The impact of questionnaire design on measurements in surveys 5 (HT-104)

Convenor Dr Natalja Menold (GESIS)
Coordinator 1Ms Kathrin Bogner (GESIS)

Questionnaire design is crucial for obtaining high-quality survey data. Still, there is a great need for research that helps to better understand how and under which conditions different design aspects of questionnaires impact measurement process and survey data quality. Therefore, researchers are invited to submit papers dealing with questionnaire design features such as question wording, visual design and answer formats, instructions, introductions and other relevant design aspects of questionnaires. Also, different means of measurement such as questions with nominal answer categories, rankings, ratings, sematic differentials or vignettes can be addressed or can be matter of comparison. Of interest is the impact of questionnaire design on response behavior, on systematic as well as non-systematic error or on validity. In addition, respondents’ cognition or motivation can be in focus of the studies.


Unit and item nonresponse 1 (HT-102)

Convenor Mr Peter Linde (Statistics Denmark)

Greater response for less money
Quality improvements frequently result in increased costs, e.g. in order to reduce nonresponse. However, nonresponse does not only depend on the number of attempts at making contact and mode, but also on the actual and experienced burden. Consequently, increased focus on reducing the experienced burden can be instrumental in increasing the achievement. The theme is discussed by examples from Statistics Denmark, where new digital solutions, better letters, prizes, reminders as to agreements, follow-up and interview training resulted in a higher degree of achievement as well as lower total costs. Concrete 6% less nonresponse and 10% less interview cost.


Using Survey Data for Spatial Analysis 2 (HT-101)

Convenor Professor Nina Baur (Technische Universität Berlin)
Coordinator 1Ms Linda Hering (Technische Universität Berlin)
Coordinator 2Ms Cornelia Thierbach (Technische Universität Berlin)

The session aims at exploring new developments in spatial methids, seeing space either as dependent or independent variable: Researchers can ask how people think about space and construct space or they can see space as a relevant frame for social action that influences social life. Papers address one of the questions below either at a more general methodological level or using a concrete example in a specific research project:

(1) How can survey data be used for spatial analysis? Can they be used by themselves, or do they have to be mixed with other data, e.g. geodata, qualitative data?

(2) What methodological innovations concerning the spatial can be observed? (How) can traditional sociological or geographical methods be adjusted to address spatial problems within sociology?

(3) Which sampling strategies are appropriate for spatial problems?

(4) Which strategies of data analysis are appropriate for spatial analysis?


Web and mixed-mode data collection in National Statistics 1 (HT-105)

Convenor Mrs Karen Blanke (FSO Germany)
Coordinator 1Mrs Annemieke Luiten (Statistics Netherlands)

Many countries within the European Statistical System (ESS) are considering web-based data collection in a system of multiple mode data collection. Eurostat initiated the ESSnet project “Data Collection in Social Surveys Using Multiple Modes” with the purpose to support Member States in their development and implementation efforts. A consortium of five NSIs has done extensive research on the development of web-based data collection tools for NSIs, specifically the Labour Force Survey, and the impact of implementing multimode data collection.
Concerning the web questionnaire, much of the work was aimed at finding out how severe the challenges in switching to self-completion actually are and if/how interviewer-assistance can be adequately replaced in web questionnaires, in view of the complicated concepts measured. The second aim was how to design functionalities in web questionnaires like instructions, routing, edit checks, customised wording or the variety of question types.
Concerning mixed mode data collection, we focussed on three issues: the organisation of mixed mode data collection, mode effects and adjustment for mode and measurement effects. In ‘organisation’ we focus on mode strategies: which modes in which sequence, response rates and measures to heighten web response. Attention is also given to the important subject of case management systems: software systems that are able to support all modes and allow flexible transitions from one mode to another. Concerning mode effects, several studies were performed on mode effects in mixed mode LFS designs. The final research topic was estimation and adjustment: given that there are mode effects, can we adjust for them, and how should that be performed.
We propose either one session where the partners in this research project discuss the findings on the topics or alternatively, we could have a double session where a number of speakers are invited to present.


Advancements of survey design in election polls and surveys 2 (N-132)

Convenor Ms Vilma Agalioti-sgompou (ISER University of Essex)

Political attitudes and behaviour are the main objects of measurement of Polls and Election Surveys. However, as it happens with surveys, they are affected from different types of error; for example, coverage error, questionnaire design effects, mode effects. Measurement error in political polls and election surveys can create different results between surveys. A distinct challenge for the researchers that aim at predicting electoral behaviour is that the reliability of the survey measurement is ‘tested’ with real electoral outcomes. This provides a unique opportunity for the validation of survey findings and examination of survey research quality.
The aim of this session is to provide a space for the latest advances in the design and development of polls and election surveys.

We welcome papers that investigate any methodological aspect of polls or surveys that:
a) measure political behaviour and/or attitudes, and,
b) provide validated information through administrative data or election outcomes.


Analyzing sexual prejudice and sexual orientation with survey data 1 (N-131)

Convenor Mrs Anabel Kuntz (University of Cologne)
Coordinator 1Dr Stephanie Steinmetz (University of Amsterdam)

In past decades, the acceptance of Lesbian, Gay, Bisexual and Transgender (LGBT) people has increased in Europe. Nevertheless, sexual prejudice considerably varies within and between European countries. Although Europe is a place where many national laws prohibit at least the incitement to discrimination based on sexual orientation, countries also differ in granting rights to LGBT people and in protecting them from discrimination. Moreover, LGBT rights are hotly debated in the European public and politics. Compared to research on other minority groups, such as ethnic minorities, sexual prejudice has been studied quantitatively much less in the social sciences. Therefore, this session aims to increase the understanding of situation of LGBT people within Europe on the basis of quantitative studies and to evaluate also the methodological challenges researchers face when using existing data sources. Contributions are welcome focusing on sexual prejudice and rights of LGBT people as well as issues relating to sexual orientation both from a substantive and methodological perspective.


Assessing and addressing measurement equivalence in cross-cultural surveys 3 (O-101)

Convenor Dr Gijs Van Houten (Eurofound)
Coordinator 1Dr Milos Kankaras (Eurofound)

Over the past decades the number of cross-cultural surveys has increased dramatically. A major challenge in cross-cultural surveys is to ensure that the answers of different respondents to survey items measure the same concepts. If measurement equivalence is not achieved it is difficult if not impossible to make meaningful comparisons across cultures and countries.

Most cross-cultural surveys aim to reduce bias by finding the right balance between harmonisation and local adaptation of the methods used in each of the stages of the surveys process (e.g. sampling, questionnaire development and translation, fieldwork implementation etc.). Furthermore, an increasing number of research projects are being carried out looking into the determinants measurement equivalence. There are three main approaches to the analysis of measurement equivalence – multigroup confirmatory factor analysis, differential item functioning, and multigroup latent class analysis. These latent variable models are based on different modelling assumptions and are appropriate for different types of data (cf. Kankaraš and Moors, 2010).

This session invites papers about the assessment of measurement equivalence in cross-cultural surveys as well as papers about efforts made to address measurement equivalence in the design and implementation of surveys. The aim is to facilitate an exchange that benefits both the future analysis of measurement equivalence and the future design of cross-national surveys.

Kankaraš, M. & Moors, G.B.D (2010). Researching measurement equivalence in cross-cultural studies. Psyhologija, 43(2) ,121-136


Big Data and Survey Research (O-201)

Convenor Mr Yamil Nares (Institute for Social & Economic Research (ISER))
Coordinator 1Dr Tarek Al Baghal (Institute for Social & Economic Research (ISER))

As the demand for data has increased in recent years, so has the potential amount of information produced by new technologies. The volume of additional behavioural data produced through people's interactions with technological innovations (smartphones, tablets, laptops), as well as the trace of people activities through emails, financial measurements, real time posts images, and videos sharing on social media (Twitter, Facebook, Google Plus, Instagram, YouTube) has garnered the name "Big Data". As the potential uses of “Big Data” seemingly provide a great opportunity to examine and study social behaviour, including changes over time, many have argued that such "Big Data" can largely replace surveys, and may be of better quality, given the problems surveys face such as increasing nonresponse. However, “Big Data” is frequently used at the macro-level, while surveys also provide micro-level data, and has more constraint on the types of information collected. To date, there have been few empirical examinations of the comparative efficacy of “Big Data” and surveys, or how these may supplement or replace the other. With the emergence of the arguments surrounding “Big Data”, given the limited amount of research conducted, it is important for social researchers to better understand the comparative and complementary aspects of these data sources, as well as data protection and privacy policies. The current panel calls for papers that examine these issues, particularly those using survey and “Big Data” in a comparative or complementary manner, examining likely sources of error and best practices. While empirical analysis will help further gain a scientific base for deciding on how to use these data better, so will papers discussing these issues theoretically. Possible issues include those of coverage, measurement, and other sources of error; examinations of how to use “Big Data” in combination with surveys; and issues of data protection.


Coding with ISCO, problems and solutions (O-106)

Convenor Professor Dominique Joye (University of Lausanne)
Coordinator 1Dr Evi Scholz (GESIS)
Coordinator 2Mrs Cornelia Zuell (GESIS)

ISCO is the mostly accepted international standard classification of occupational codings, often used in long-standing high quality cross-national surveys. ISCO serves to classify jobs into a clearly defined set of groups according to the tasks and duties in jobs. Due to the long list of hundreds of categories and definitions reflected in the four digits needed for classification, coding of occupations is a challenging enterprise. While categories are exactly defined and mutual exclusive, coding is difficult due to the unclear or incomplete answers of respondents who are not familiar with ISCO, in particular at the most detailed level. ISCO is used to attribute people in class schema as well as attribute scores describing respondents’ position in society.

The proposed session aims at bringing together national and comparative researchers interested in
- the measurement of occupations (mode, question design, etc.);
- techniques of coding ISCO (automatic coding, semi-automatic coding, manual coding);
- problems of coding ISCO (costs, validity, reliability, etc.);
- alternative occupational ISCO coding (e.g., pseudo-ISCO);
- cross-national issues and links to national classification or national tradition;
- ISCO in longitudinal perspective;
- other methodological aspects related to ISCO coding, including coding and measuring of social position in national contexts.

The core of the discussion will be on ISCO08 but contributions based on ISCO88 or earlier are also wellcome.


Cognition in surveys 1 (O-206)

Convenor Dr Bregje Holleman (Utrecht University)
Coordinator 1Dr Naomi Kamoen (Utrecht University/ Tilburg University)

Cognitive research in surveys covers a wide range of approaches. In recent years, various models describing the cognitive processes underlying question answering in standardized surveys have been proposed. A lot of research is guided by the model of question answering by Tourangeau, Rips and Rasinski (2000). This model distinguishes four stages in question answering: (1) comprehension of the question, (2) retrieval of information, (3) deriving a judgment, and (4) formulating a response. In addition, there are dual-process models, such as the satisficing model proposed by Krosnick (1991). In this model, two groups of respondents are distinguished: those who satisfice, and try to do just enough to give a plausible answer versus those who optimize, and do their best to give a good answer.

Cognitive models such as the two described above, have many applications. For example, they help in understanding what is measured when administering surveys, and they provide a point of departure in explaining the wide range of method effects survey researchers observe. Also, cognitive theory in surveys is used by psychologists, linguists and other scholars to obtain a deeper understanding of, for example, language processing, the nature of attitudes, and memory.

Recently, similar cognitive approaches are also used to describe the ways attitudes are formed using standardized surveys. In this type of research, so-called 'decision aids', such as Voting Advice Applications (VAAs), are studied. In VAAs, users answer attitude questions about political issues in order to obtain a voting advice. How do design choices in these decision aids affect users' answers, attitudes and behavioral intentions?

We cordially invite researchers addressing one or more of these topics to submit their papers to this session.


Going beyond the basics of questionnaire design: new and innovative approaches to instrument design in web surveys 1 (HT-104)

Convenor Dr Femke De Keulenaer (Ipsos)
Coordinator 1Professor Edith De Leeuw (Utrecht University)
Coordinator 2Mr Arnaud Wijnant (CentERdata / Tilburg University)

Web questionnaires can differ substantially from questionnaires in traditional modes; nonetheless, most web-based instruments are based on classic text-based questionnaire principles. Rather than simply applying the design principles for paper questionnaires, researchers could capitalize on the unique properties of the web interaction. In web surveys, the medium can be fully exploited to produce better ways of asking and answering questions, and to introduce new approaches to surveying (i.e. going beyond “asking questions”).

In this session, we would like to focus on the potential for advanced questionnaire design in web surveys and innovative approaches to surveying respondents. Topics could include, but are not limited to the following:

- The unique properties of web interaction can be used to design web questionnaire interfaces that adapt or tailor themselves to respondents’ behaviour, diagnose respondents’ need for clarification, detect respondents’ lack of effort, etc.

- A difference between web surveys and traditional surveys can be the focus on (audio-)visual communication. The dynamic and graphical nature of the web has led to the creation of a wide range of measurement tools that previously could not be done on paper; examples include card sort tasks, interactive maps and verbal information.

- Web surveys also offer possibilities for innovative approaches to surveying; for example, behavioural experiments have made the switch from asking respondents to report on their behaviour (via survey questions) to actually observing respondent behaviour (e.g. using game-enhanced instruments or facial expression devices).

- This type of innovative approaches to web instrument design, however, can also lead to a variety of unpredicted effects that reduce the quality of web-based surveys. Researchers are also invited to present empirical evaluations and split ballot experiments. Only by fully understanding both the benefits - and the drawbacks – of innovations can we fully exploit the potential of web surveys.


Longitudinal surveys - challenges in running panel studies 3 (O-202)

Convenor Dr Jutta Von Maurice (Leibniz Institute for Educational Trajectoires)
Coordinator 1Ms Joanne Corey (Australian Bureau of Statistics)

Longitudinal surveys - challenges in running panel studies.

This session will focus on the organisation of panel studies, including panel maintenance, panel engagement, sample review processes, choice of data items and methodologies, and interviewer training.

The focus is on the particular challenges faced by those running panel studies such as:

. maintaining up-to-date contact information and tracking of respondents, including privacy concerns;

. engaging repsondents over the life of the survey, particularly for different age groups, for example how to keep young people interested as they move from children to young adults and they become the primary consenter;

. how successful are different modes for making contact, e.g. mail, phone, text;

. do targeted approach stategies work, e.g. different approach letters depending on past wave response;

. decision making guidelines about when a respondent should be removed from the sample;

. the debate between longitudinal consistency and using a better/updated measure;

. how to conduct training for a mix of experienced and new interviewers, balanced with the amount of new content and methodologies; and

.testing techniques for longitudinal surveys.


Measuring Social Networks in Large-Scale Surveys: Challenges and Practice of Ego-Centred and Complete Network Approaches 1 (HT-101)

Convenor Mr Benjamin Schulz (Mannheim Centre for European Social Research and WZB Berlin Social Science Center)
Coordinator 1Mrs Kerstin Hoenig (Leibniz-Institute for Educational Trajectories (LIfBi), Bamberg)
Coordinator 2Professor Reinhard Pollak (WZB Berlin Social Science Center and Freie Universität Berlin)

Survey researchers measure social networks in two fundamental ways: i) in an ego-centred manner that captures an actor’s ties and related characteristics, ii) in a broader way that captures complete networks within predefined boundaries. The latter approach gains increasing attention as recent projects in many countries and fields collect complete network data.
This increase largely follows from advances in survey instruments for complete networks and in statistical modelling, especially for network dynamics. Methodologically, complete network analysis makes it possible to separate selection and influence processes. These surveys, however, are mainly conducted in schools as meaningful network boundaries are easy to implement in this context.
Ego-centred measures offer the chance to collect network data in contexts where a complete network measurement is not feasible. To meet the challenge of reversed causality and endogeneity as a consequence of the non-random, often homophilous, formation of social ties, panel data including repeated, or prospective and retrospective, measures are promising. Several international large-scale surveys made significant progress in this domain.
By bringing together researchers from both camps, we seek to promote a discussion that allows for a better evaluation of the advantages and pitfalls of each approach. The session's focus shall be on longitudinal measurements and statistical modelling of social networks, especially on means to identify causal network effects. The second focus shall be on ways to assess the reliability and validity of ego-centred and complete network measures. For ego-centred network measures, such as name or resource generators, the reliability of these instruments will be of central interest. For complete network measures, the specification of network boundaries is a heavily debated issue. Contributions might also include studies on how to identify and deal with compositional changes or on inference errors that may follow from insufficiently specified boundaries.


Methodological issues of using administrative data to improve the quality of survey data 1 (HT-103)

Convenor Dr Emanuela Sala (Dipartimento di Sociologia e Ricerca Sociale, Università di MIlano Bicocca)
Coordinator 1Dr Jonathan Burton (ISER, University of Essex)
Coordinator 2Dr Gundi Knies (ISER, University of Essex)

There is a body of research on eliciting respondents' consent to link their survey data to their administrative records. However, the process of linking survey and administrative data is complex and the issues that survey practitioners need to tackle go beyond the asking for respondents' consent. Furthermore, using that linked data also provides potential for further methodological research. The aim of this session is to foster discussion on i) methodological issues that concern the data linkage process, ii) the research potential of the linked data,
iii) use of administrative data to improve the quality of survey data

We welcome papers on the following topics:

1. Analysis of mis-reporting
2. Measurement 'bias' using linked data
3. Impact on research findings compared to using survey data only
4. Validation studies
5. Methodological lessons from linkage process
6. Implications of consent bias

Relevant papers on other aspects of data linkage will also be considered.


Mixed methods designs combining survey data and qualitative data 1 (L-102)

Convenor Professor Mark Trappmann (Institute for Employment Research (IAB))
Coordinator 1Dr Andreas Hirseland (Institute for Employment Research (IAB))

In social science research there is a long tradition of research combining survey data with qualitative data. There can be various reasons why this integration of approaches provides advantages compared to a single method approach and how it is implemented in a research design. Greene et al. (1989) propose a typology consisting of five types of mixed-method designs. Triangulation involves investigating the same aspect of the same phenomenon. If research methods bias results, there is a chance of detecting this bias by using different methods independently. In contrast, complementarity involves investigating different aspects of the same phenomenon by different methods. Results from one method are used to elaborate, enhance, or illustrate results from the other. Development designs sequentially use one method to develop or support the other method. Examples include using qualitative interviews in questionnaire design or residual diagnostics or to use quantitative survey data for theoretical sampling in qualitative research. Initiation designs aim at uncovering paradox or contradictions to initiate new insights. Finally, expansion designs extend the scope of a study by mixing methods. One typical example of this last approach is the combination of quantitative evaluation of programme outcomes with qualitative studies of programme implementation. We encourage submissions dealing with designs of mixed-methods studies combining survey research and qualitative research. Presentations should focus on methodological issues of research designs or analysis of such data.


Response rates and nonresponse bias in comparative surveys 1 (HT-102)

Convenor Dr Koen Beullens (KU Leuven)
Coordinator 1Dr Ineke Stoop (SCP)

Comparing response rates and possibly associated nonresponse bias can be hard in the context of cross-national surveys. First, response rates objectives may be set differently. In this respect, the European Social Survey sets a 70% response rate objective, without really penalizing countries that do not achieve this objective. PIAAC, on the other hand, also sets a target response rate of of 70%, but accepts response rates in between 50% to 70%, whereas when response rates below 50% occur a nonresponse analysis has to be provided. Second, response rates have to be calculated in a comparable ways. Response rates from EU-SILC and the LFS, for instance, are sometimes hard to compare because the numerator and/or denominator may be calculated in different ways. Third, and even more complicated, are the national differences regarding survey design features (e.g. sampling design) that have diverse implication for the response and the nonresponse bias.

Not only is it hard to determine nonresponse bias for a single survey, the cross-national context even adds more complexity, probably strongly jeopardizing the comparability between countries or surveys. The survey climate in different countries, the related nonresponse mechanisms, strategies to minimize nonresponse (bias) or adjustment methods are not likely to be considered as uniform over different countries or surveys.

Therefore, this session welcomes papers on (1) enhancing response, (2) fieldwork strategies minimising nonresponse bias and (3) nonresponse adjustment methods, all providing better comparability for cross-national surveys.


Surveying children and young people 1 (L-103)

Convenor Miss Emily Gilbert (Centre for Longitudinal Studies, Institute of Education)
Coordinator 1Ms Lisa Calderwood (Centre for Longitudinal Studies, Institute of Education)

Many large-scale surveys successfully collect a variety of different types of data from children and young people. However, there is relatively little methodological evidence in this area. Much of the literature relating to children and young people’s participation in research focuses on small-scale qualitative studies and tends to concentrate on ethical issues relating to the rights of children and young people in research. This session will cover experiences of including children and young people in surveys, and related survey design issues. The session aims to explore a variety of methodological issues around surveying children and young people. Submissions are particularly welcomed on:
- designing questionnaires for children and young people, including question testing methods
- collecting sensitive data from children and young people, including methods for ensuring privacy and encouraging accurate reporting
- collecting different types of data from children and young people, including physical measurements, cognitive assessments, biological samples and time use data
- using different methods of data collection, including the use of innovative technology such as the web and mobile phones
- inclusivity in data collection methods, including facilitating the participation of young people with lower literacy levels
- assessing the reliability and validity of young people’s self-reports
- preventing non-response by engaging young people in research, including designing survey materials to appeal to young people and using new technology and digital media for participant engagement
- ethical issues in involving children and young people in surveys, including gaining informed consent and protecting children’s rights and well-being


Web and mixed-mode data collection in National Statistics 2 (HT-105)

Convenor Mrs Karen Blanke (FSO Germany)
Coordinator 1Mrs Annemieke Luiten (Statistics Netherlands)

Many countries within the European Statistical System (ESS) are considering web-based data collection in a system of multiple mode data collection. Eurostat initiated the ESSnet project “Data Collection in Social Surveys Using Multiple Modes” with the purpose to support Member States in their development and implementation efforts. A consortium of five NSIs has done extensive research on the development of web-based data collection tools for NSIs, specifically the Labour Force Survey, and the impact of implementing multimode data collection.
Concerning the web questionnaire, much of the work was aimed at finding out how severe the challenges in switching to self-completion actually are and if/how interviewer-assistance can be adequately replaced in web questionnaires, in view of the complicated concepts measured. The second aim was how to design functionalities in web questionnaires like instructions, routing, edit checks, customised wording or the variety of question types.
Concerning mixed mode data collection, we focussed on three issues: the organisation of mixed mode data collection, mode effects and adjustment for mode and measurement effects. In ‘organisation’ we focus on mode strategies: which modes in which sequence, response rates and measures to heighten web response. Attention is also given to the important subject of case management systems: software systems that are able to support all modes and allow flexible transitions from one mode to another. Concerning mode effects, several studies were performed on mode effects in mixed mode LFS designs. The final research topic was estimation and adjustment: given that there are mode effects, can we adjust for them, and how should that be performed.
We propose either one session where the partners in this research project discuss the findings on the topics or alternatively, we could have a double session where a number of speakers are invited to present.


Analyzing sexual prejudice and sexual orientation with survey data 2 (N-131)

Convenor Mrs Anabel Kuntz (University of Cologne)
Coordinator 1Dr Stephanie Steinmetz (University of Amsterdam)

In past decades, the acceptance of Lesbian, Gay, Bisexual and Transgender (LGBT) people has increased in Europe. Nevertheless, sexual prejudice considerably varies within and between European countries. Although Europe is a place where many national laws prohibit at least the incitement to discrimination based on sexual orientation, countries also differ in granting rights to LGBT people and in protecting them from discrimination. Moreover, LGBT rights are hotly debated in the European public and politics. Compared to research on other minority groups, such as ethnic minorities, sexual prejudice has been studied quantitatively much less in the social sciences. Therefore, this session aims to increase the understanding of situation of LGBT people within Europe on the basis of quantitative studies and to evaluate also the methodological challenges researchers face when using existing data sources. Contributions are welcome focusing on sexual prejudice and rights of LGBT people as well as issues relating to sexual orientation both from a substantive and methodological perspective.


Cognition in surveys 2 (O-206)

Convenor Dr Bregje Holleman (Utrecht University)
Coordinator 1Dr Naomi Kamoen (Utrecht University/ Tilburg University)

Cognitive research in surveys covers a wide range of approaches. In recent years, various models describing the cognitive processes underlying question answering in standardized surveys have been proposed. A lot of research is guided by the model of question answering by Tourangeau, Rips and Rasinski (2000). This model distinguishes four stages in question answering: (1) comprehension of the question, (2) retrieval of information, (3) deriving a judgment, and (4) formulating a response. In addition, there are dual-process models, such as the satisficing model proposed by Krosnick (1991). In this model, two groups of respondents are distinguished: those who satisfice, and try to do just enough to give a plausible answer versus those who optimize, and do their best to give a good answer.

Cognitive models such as the two described above, have many applications. For example, they help in understanding what is measured when administering surveys, and they provide a point of departure in explaining the wide range of method effects survey researchers observe. Also, cognitive theory in surveys is used by psychologists, linguists and other scholars to obtain a deeper understanding of, for example, language processing, the nature of attitudes, and memory.

Recently, similar cognitive approaches are also used to describe the ways attitudes are formed using standardized surveys. In this type of research, so-called 'decision aids', such as Voting Advice Applications (VAAs), are studied. In VAAs, users answer attitude questions about political issues in order to obtain a voting advice. How do design choices in these decision aids affect users' answers, attitudes and behavioral intentions?

We cordially invite researchers addressing one or more of these topics to submit their papers to this session.


Cultural Response Styles (O-101)

Convenor Professor Martin Weichbold (University of Salzburg)
Coordinator 1Professor Nina Baur (TU Berlin)
Coordinator 2Dr Wolfgang Aschauer (University of Salzburg)

Cross-national and cross-cultural surveys are facing numerous challenges at different stages of the research process. Despite the broad research on potential methodological biases during fieldwork, there are still some fields which gain less attention although they contain a considerable risk of biasing survey data. Various measurement errors (such as social desirability or acquiescence) have been high on the research agenda in survey methodology for a long time, but there are only a few studies on differences of these effects between cultures or nations.
Cultural imprints are a particular threat to the comparability of scales and indicators because we have to assume different levels and/or patterns of response styles in different countries. Challenges posed by cultural response styles have always been highly relevant in the increasing amount of cross-national research but there is growing importance of those potential biases for surveys in single nations as well – due to the growing number of people with immigrant background (at least in European countries). It seems obvious that the prevalence of response styles is related to other cultural patterns and certain contextual data, but there is hardly any systematic research and only sporadic empirical findings.
For the proposed session on cultural response styles we ask researchers for contributions covering one or more of the following topics:
- Providing empirical evidence of differences of response styles in surveys between countries or within countries (between different cultures)
- Searching for certain explanations for this differences (at the individual or contextual level)
- Looking for strategies how to deal with cultural response styles in cross-national surveys


Effects of respondent incentives in Health Interview Surveys. Differences according to survey modes, incentive strategies and incentive values 1 (O-202)

Convenor Dr Elena Von Der Lippe (Robert Koch Institute)
Coordinator 1Mr Patrick Schmich (Robert Koch Insitute)
Coordinator 2Mr Matthias Wetzstein (Robert Koch Institute)

Respondent incentives as one possible mean of raising response rates is broadly used in social science. It is often reported that the respondent incentives have different impact on various sub-population groups under study. Also, incentive effects vary according to the survey modes and strategies applied. Research shows that the value of the respondent incentives has to be well considered, as not always higher values lead to higher response rates.
The aim of this session is to gather and exchange experiences in applying incentive strategies in health interview surveys and also other population based surveys. One of the sample biases that are often faced in health interview surveys is the higher participation of respondents with high education level. Applying any incentive strategy would aim at reaching the population that otherwise is not willing to participate in health interview surveys.
We would like to welcome presentations dealing with the application of any kind of incentive strategies in health interview surveys, regardless of the survey mode used. In particular, we are interested in reporting: what kind of incentive strategies (e.g. monetary or non-monetary) show significant effects on the response rates; did the incentives have the same effects for different sub-population groups (e.g. urban/rural, young/old population); did the usage of incentives lead also to a better sample composition and reduction in the sample bias; what incentive strategies and values are balancing best between costs and effects?


Going beyond the basics of questionnaire design: new and innovative approaches to instrument design in web surveys 2 (HT-104)

Convenor Dr Femke De Keulenaer (Ipsos)
Coordinator 1Professor Edith De Leeuw (Utrecht University)
Coordinator 2Mr Arnaud Wijnant (CentERdata / Tilburg University)

Web questionnaires can differ substantially from questionnaires in traditional modes; nonetheless, most web-based instruments are based on classic text-based questionnaire principles. Rather than simply applying the design principles for paper questionnaires, researchers could capitalize on the unique properties of the web interaction. In web surveys, the medium can be fully exploited to produce better ways of asking and answering questions, and to introduce new approaches to surveying (i.e. going beyond “asking questions”).

In this session, we would like to focus on the potential for advanced questionnaire design in web surveys and innovative approaches to surveying respondents. Topics could include, but are not limited to the following:

- The unique properties of web interaction can be used to design web questionnaire interfaces that adapt or tailor themselves to respondents’ behaviour, diagnose respondents’ need for clarification, detect respondents’ lack of effort, etc.

- A difference between web surveys and traditional surveys can be the focus on (audio-)visual communication. The dynamic and graphical nature of the web has led to the creation of a wide range of measurement tools that previously could not be done on paper; examples include card sort tasks, interactive maps and verbal information.

- Web surveys also offer possibilities for innovative approaches to surveying; for example, behavioural experiments have made the switch from asking respondents to report on their behaviour (via survey questions) to actually observing respondent behaviour (e.g. using game-enhanced instruments or facial expression devices).

- This type of innovative approaches to web instrument design, however, can also lead to a variety of unpredicted effects that reduce the quality of web-based surveys. Researchers are also invited to present empirical evaluations and split ballot experiments. Only by fully understanding both the benefits - and the drawbacks – of innovations can we fully exploit the potential of web surveys.


How to measure political participation? (N-132)

Convenor Dr Christina Eder (GESIS)
Coordinator 1Professor Isabelle Stadelmann-steffen (Universität Bern)

Political participation is the heart of modern democracy. From voting to writing to one’s representative, wearing a badge, becoming a party member, attending a demonstration to boycotting a product or occupying a building, each citizen has various opportunities to voice her opinion. Hence, there is a correspondingly rich literature on all kinds of political participation. Yet, (comparative) researchers in this area are often faced by at least one of the following challenges: a) relevant questions are not included in the survey program(s) one employs or the question wording varies across surveys, countries and/or time. This is particularly true for the more unconventional, elite-challenging and bottom-up forms of citizen involvement. b) Cross-national surveys encounter the difficulty of some kinds of participation, like ‘signing a petition’ for instance, meaning different things in different countries. c) Survey responses might be biased by social desirability, with the participants tending to claim that they have used more means than they actually did.

The proposed session is a forum to discuss and evaluate ways to deal with these challenges from different perspectives. It strives to bring together primary investigators, data collectors and users of secondary data. We therefore welcome papers investigating the above mentioned aspects from a theoretical or methodological angle as well as manuscripts using a more applied or experimental approach.


Measuring Social Networks in Large-Scale Surveys: Challenges and Practice of Ego-Centred and Complete Network Approaches 2 (HT-101)

Convenor Mr Benjamin Schulz (Mannheim Centre for European Social Research and WZB Berlin Social Science Center)
Coordinator 1Mrs Kerstin Hoenig (Leibniz-Institute for Educational Trajectories (LIfBi), Bamberg)
Coordinator 2Professor Reinhard Pollak (WZB Berlin Social Science Center and Freie Universität Berlin)

Survey researchers measure social networks in two fundamental ways: i) in an ego-centred manner that captures an actor’s ties and related characteristics, ii) in a broader way that captures complete networks within predefined boundaries. The latter approach gains increasing attention as recent projects in many countries and fields collect complete network data.
This increase largely follows from advances in survey instruments for complete networks and in statistical modelling, especially for network dynamics. Methodologically, complete network analysis makes it possible to separate selection and influence processes. These surveys, however, are mainly conducted in schools as meaningful network boundaries are easy to implement in this context.
Ego-centred measures offer the chance to collect network data in contexts where a complete network measurement is not feasible. To meet the challenge of reversed causality and endogeneity as a consequence of the non-random, often homophilous, formation of social ties, panel data including repeated, or prospective and retrospective, measures are promising. Several international large-scale surveys made significant progress in this domain.
By bringing together researchers from both camps, we seek to promote a discussion that allows for a better evaluation of the advantages and pitfalls of each approach. The session's focus shall be on longitudinal measurements and statistical modelling of social networks, especially on means to identify causal network effects. The second focus shall be on ways to assess the reliability and validity of ego-centred and complete network measures. For ego-centred network measures, such as name or resource generators, the reliability of these instruments will be of central interest. For complete network measures, the specification of network boundaries is a heavily debated issue. Contributions might also include studies on how to identify and deal with compositional changes or on inference errors that may follow from insufficiently specified boundaries.


Methodological issues of using administrative data to improve the quality of survey data 2 (HT-103)

Convenor Dr Emanuela Sala (Dipartimento di Sociologia e Ricerca Sociale, Università di MIlano Bicocca)
Coordinator 1Dr Jonathan Burton (ISER, University of Essex)
Coordinator 2Dr Gundi Knies (ISER, University of Essex)

There is a body of research on eliciting respondents' consent to link their survey data to their administrative records. However, the process of linking survey and administrative data is complex and the issues that survey practitioners need to tackle go beyond the asking for respondents' consent. Furthermore, using that linked data also provides potential for further methodological research. The aim of this session is to foster discussion on i) methodological issues that concern the data linkage process, ii) the research potential of the linked data,
iii) use of administrative data to improve the quality of survey data

We welcome papers on the following topics:

1. Analysis of mis-reporting
2. Measurement 'bias' using linked data
3. Impact on research findings compared to using survey data only
4. Validation studies
5. Methodological lessons from linkage process
6. Implications of consent bias

Relevant papers on other aspects of data linkage will also be considered.


Mixed methods designs combining survey data and qualitative data 2 (L-102)

Convenor Professor Mark Trappmann (Institute for Employment Research (IAB))
Coordinator 1Dr Andreas Hirseland (Institute for Employment Research (IAB))

In social science research there is a long tradition of research combining survey data with qualitative data. There can be various reasons why this integration of approaches provides advantages compared to a single method approach and how it is implemented in a research design. Greene et al. (1989) propose a typology consisting of five types of mixed-method designs. Triangulation involves investigating the same aspect of the same phenomenon. If research methods bias results, there is a chance of detecting this bias by using different methods independently. In contrast, complementarity involves investigating different aspects of the same phenomenon by different methods. Results from one method are used to elaborate, enhance, or illustrate results from the other. Development designs sequentially use one method to develop or support the other method. Examples include using qualitative interviews in questionnaire design or residual diagnostics or to use quantitative survey data for theoretical sampling in qualitative research. Initiation designs aim at uncovering paradox or contradictions to initiate new insights. Finally, expansion designs extend the scope of a study by mixing methods. One typical example of this last approach is the combination of quantitative evaluation of programme outcomes with qualitative studies of programme implementation. We encourage submissions dealing with designs of mixed-methods studies combining survey research and qualitative research. Presentations should focus on methodological issues of research designs or analysis of such data.


Mixing modes and mode effects (HT-105)

Convenor Mrs Caroline Bayart (University Lyon 1)
Coordinator 1Mr Patrick Bonnel (University Lyon 2 - ENTPE)

Survey response rates are decreasing over the world. Even if weighting procedures allow to reduce the incidence of non-response, it is always necessary to postulate that people with some socio-demographic characteristics who do not respond to a survey have the same behaviour than people with the same socio-demographic characteristics who respond. But evidence seems to indicate that it is not always the case and survey non-response might produce bias. Efforts are made to increase response rate for traditional survey by improving the questionnaire, reducing respondent burden, increasing reminders… Even if results are generally positive, it is in most cases not sufficient.
A way to balance the impact of non-response and produce more reliable results, is to propose different media and let people chose the apppropriate mode and moment to answer. The potential of new and interactive media seems to be high to collect data. But these solutions generates some bias. First, in terms of design and administration of the questionnaire, which could vary according to the mode. Then, the generalization of the results to the whole population sometimes is an issue. Lastly, the question of data comparability remains. When mixed survey modes are used, individuals choose to belong to one group or another or only respond if the proposed medium suits them. The responses are therefore not completely comparable, because the sample is no longer random and the presence of respondents is determined by external factors, which may also affect the variable of interest in the studied model. The danger when databases are merged is that a sample selection bias will be created and compromise the accuracy of explanatory models.
The aim of the session is to to characterize bias generated by mixed modes surveys and give some perspectives for reduce them.


Multilevel survey research, agent based modeling and social mechanisms: towards new frontiers in theory-based empirical research (L-101)

Convenor Dr Dominik Becker (Heinrich Heine University Düsseldorf)
Coordinator 1Dr Tilo Beckers (Heinrich Heine University Düsseldorf)
Coordinator 2Professor Ulf Tranow (Heinrich Heine University Düsseldorf)

This three-part session will lay the spotlight on the link between empirically-oriented theories and empirical research by focusing on the explanatory concept of social mechanisms. When explaining macro-level phenomena such as network structures or social diffusion outcomes, establishing the underlying social mechanisms is a strategy to overcome incomplete explanations which remain restricted on the macro level. Instead, the theoretical and empirical objective is to unveil the meso- or micro-level social mechanisms causing the macro-level explananda. Whether following Coleman’s explanatory macro-micro-macro model, (`wide´) rational action theory or DBO theory (desires, beliefs and opportunities), social scientists address the need for more fine-grained explanatory approaches.

Since about two decades, social mechanism research evolves to be an important paradigm in the social sciences. Yet, though survey data allow for and are often used to study social mechanisms, their methodological potential to do so is only rarely addressed systematically.

In part 1, we invite colleagues establishing social mechanisms as part of their theoretical explanation and actually researching these mechanisms applying different survey research designs. In part 2, we would like to bring together researchers using survey (and/or network) data and linking them to agent-based modeling, an approach which will gain importance to extend and enrich the use of survey data. In part 3, we invite presenters discussing either specific micro- or macro-based mechanisms, i.e. both survey-based and experimental approaches (including mediation and moderation analyses) as well as process tracing. We particularly welcome papers applying multilevel mechanism research, e.g. explicating cross-level interaction effects, or controlling for group-induced selection biases and linking analytical theoretical arguments with their data.

Abstracts should include theoretical references, a specification of the mechanism(s) under study and the method and type of data and analyses.


Response rates and nonresponse bias in comparative surveys 2 (HT-102)

Convenor Dr Koen Beullens (KU Leuven)
Coordinator 1Dr Ineke Stoop (SCP)

Comparing response rates and possibly associated nonresponse bias can be hard in the context of cross-national surveys. First, response rates objectives may be set differently. In this respect, the European Social Survey sets a 70% response rate objective, without really penalizing countries that do not achieve this objective. PIAAC, on the other hand, also sets a target response rate of of 70%, but accepts response rates in between 50% to 70%, whereas when response rates below 50% occur a nonresponse analysis has to be provided. Second, response rates have to be calculated in a comparable ways. Response rates from EU-SILC and the LFS, for instance, are sometimes hard to compare because the numerator and/or denominator may be calculated in different ways. Third, and even more complicated, are the national differences regarding survey design features (e.g. sampling design) that have diverse implication for the response and the nonresponse bias.

Not only is it hard to determine nonresponse bias for a single survey, the cross-national context even adds more complexity, probably strongly jeopardizing the comparability between countries or surveys. The survey climate in different countries, the related nonresponse mechanisms, strategies to minimize nonresponse (bias) or adjustment methods are not likely to be considered as uniform over different countries or surveys.

Therefore, this session welcomes papers on (1) enhancing response, (2) fieldwork strategies minimising nonresponse bias and (3) nonresponse adjustment methods, all providing better comparability for cross-national surveys.


Survey Research in Developing Countries 4 (L-103)

Convenor Dr Irene Pavesi (Small Arms Survey)

This session explores the challenges involved in conducting survey research in developing countries and discuss best practices in sampling, questionnaire design and fieldwork organisation.

Even more often than in developed countries up-to-date data on population size and composition is absent. Mobile populations, scarcely populated areas and areas connected only by low quality roads and security issues complicate the creation of a sampling frame. What strategies have researchers used to deal with these challenges?

Response rates tend to be high in developing countries. This is in part because in rural areas trust tends to be high or a survey is seen as an interesting break from everyday life. However in some cases the consent of village heads or other local leaders is an order to people to participate. How does this fit with the idea of informed consent?

High poverty in some areas raises ethical questions on whether and how respondents should be compensated for their time; if respondents receive cash or in kind compensation this can lead to competition among households for inclusion in the survey. What are appropriate ways to compensate respondents?

Large household with complex structures can make collection of household data a time consuming and error prone process. How can data be collected in an efficient way?

High ethnic and linguistic diversity poses challenges to both questionnaire translation and selection of interviewers. How can these challenges be dealt with?

If the people who design the questionnaire are not from the country of data collection, what procedures can be used to ensure that concepts in the survey resonate with those of the target population?

We welcome papers on these and related topics, such as reaching female respondents, use of ICT in data collection, surveying in (post-)conflict areas, and surveys among populations with high illiteracy rates


Comparability in International Comparative Research (O-101)

Convenor Dr Katarzyna M. Staszynska (Kozminski University)

The session would be devoted to the problems of comparability of data gathered in international comparative research. The limitations of comparability might be of various origin:

Linguistic. The rules of conducting international comparative research require detail translation of the research questionnaires into native languages of participant countries. The problem of lacking the translation that takes into account cultural differences between countries/ethnic groups (various understandings of terms, for instance: “democracy” is differently understood in Western societies where it has a positive meaning while in some Eastern societies might easily be associated with social disorder; “happiness” in some societies might be understood as individual material well being, good family life and love while in others - relationship of an individual with God, successful meditation and self-acceptance);
Related to social structure and stratification. The rules of social behaviors are strongly attached to social position of an individual. On some social positions particular behaviors might be considered inappropriate. During an interview people on some social positions might easily hide their own attitudes and opinions because in a particular culture they are not expected to present their own, individual points of view but rather a point of view of a strata they belong to.
Gender related. In some societies/ethnic groups women cannot be interviewed by male interviewers and men should rather not be interviewed by female interviewers. Since the interviewer effect is well recognized, the fact that male and female interviewers interview respondents of the same gender might be a reason of biased data.

Not all of the barriers for comparability of data gathered in international comparative research have been listed in here. We are open to hear the experiences of researchers running survey research in various societies and cultures.


Effects of respondent incentives in Health Interview Surveys. Differences according to survey modes, incentive strategies and incentive values 2 (O-202)

Convenor Dr Elena Von Der Lippe (Robert Koch Institute)
Coordinator 1Mr Patrick Schmich (Robert Koch Insitute)
Coordinator 2Mr Matthias Wetzstein (Robert Koch Institute)

Respondent incentives as one possible mean of raising response rates is broadly used in social science. It is often reported that the respondent incentives have different impact on various sub-population groups under study. Also, incentive effects vary according to the survey modes and strategies applied. Research shows that the value of the respondent incentives has to be well considered, as not always higher values lead to higher response rates.
The aim of this session is to gather and exchange experiences in applying incentive strategies in health interview surveys and also other population based surveys. One of the sample biases that are often faced in health interview surveys is the higher participation of respondents with high education level. Applying any incentive strategy would aim at reaching the population that otherwise is not willing to participate in health interview surveys.
We would like to welcome presentations dealing with the application of any kind of incentive strategies in health interview surveys, regardless of the survey mode used. In particular, we are interested in reporting: what kind of incentive strategies (e.g. monetary or non-monetary) show significant effects on the response rates; did the incentives have the same effects for different sub-population groups (e.g. urban/rural, young/old population); did the usage of incentives lead also to a better sample composition and reduction in the sample bias; what incentive strategies and values are balancing best between costs and effects?


Estimating effects of modes and mixed modes designs 2 (HT-105)

Convenor Mr Alexandru Cernat (Institute for Social and Economic Research, University of Essex)

Traditional approaches to data collection in the social sciences (i.e., face to face and telephone surveys) are becoming more expensive. At the same time cheaper approaches, such as web surveys, lack traditional sampling frames. This has led to a surge in data collection designs that aim to combine the strength of each mode into a single survey. In this context, accumulating evidence that informs design decision in mixed modes surveys is essential.

This session will contribute to this debate by tackling some important topics such as:
- Is the effect of social desirability moderated by mode?
- How do self-administered strategies (e.g., paper and web) differ in data quality?
- Are traditional scales (like those measuring personality, depression, cognitive ability) equivalent across modes?
- How does selection/non-response bias differ across modes?
- Does the use of mixed mode data impact substantive results?
- How does research on mixed mode integrate in the Total Survey Error framework?
- How to prevent mode effects through design?


Methodological Aspects of the Left-right Self-placement Scale (N-132)

Convenor Ms Cornelia Zuell (GESIS)
Coordinator 1Dr Evi Scholz (GESIS)

The left-right dimension is a core element of political science research, serving as an instrument that supports citizens’ orientations in a complex political world by condensing political contents. Analyses of the left-right dimension are usually based on responses to a left-right self-placement scale, and sometimes to open-ended questions about the meaning of left and right. Left-right self-placement on a uni-dimensional scale is a standard type of survey question that measures respondents’ ideological orientations in a minimalist way. Aspects that are taken into account are the context and the way the scale is traditionally calibrated or methodological aspects, e.g., offering a midpoint or a “can’t choose” option, or cross-cultural differences in understanding the scale by the respondents.

The proposed session aims at bringing together national and comparative researchers interested in
- the design of the left-right scale (for example, scale range, scale labels, use of midpoint, use of permitted “don’t know”, mode effects);
- methodological aspects of response behavior to the left-right scale or to open-ended questions;
- the use of probe question, for example, about the meaning of left and right or about reasons for selecting the midpoint;
- response bias and social desirability;
- cross-national equivalence (left-right; liberal-conservative) and comparability;
- other methodological aspects related to the left-right self-placement.


Mixing Survey and Qualitative Data 1 (L-102)

Convenor Professor Nina Baur (Technische Universität Berlin)
Coordinator 1Dr Leila Akremi (Technische Universität Berlin)
Coordinator 2Ms Melanie Wenzel (Technische Universität Berlin)

The session invites papers that discuss how to mix survey data with qualitative data, e.g. qualitative interviews, ethnography, video analysis etc. Presenters are specifically asked to discuss what methodlogical problems they faced and how they handled them.


Multilevel Models for the Analysis of Comparative (Longitudinal) Survey Data 1 (L-101)

Convenor Dr Alexander Schmidt-catran (Institute of Sociology and Social Psychology, University of Cologne)
Coordinator 1Professor Bart Meuleman (Centre for Sociological Research, University of Leuven)

Multilevel models have become predominant in analyses of comparative survey datasets, where respondents are clustered in higher-level units like countries or regions. Such models have also long been fitted to longitudinal data, where repeated observations are clustered within units. Additionally, researchers are fitting multilevel models to data that are clustered both ways, such as multiple waves of surveys whose respondents are nested in countries or regions each observed multiple times. These comparative longitudinal survey datasets should be useful resources for studies of social change in the broadest sense, and for drawing inferences previously based on only cross-sectional analyses. This session welcomes papers using multilevel models for the analysis of cross-sectional data, longitudinal data and, in particular, data that is clustered both ways. Papers might address recent methodological advances; present illuminating or innovative applications in some field of the social sciences; and/or discuss limitations and challenges that remain.


New sources of data for survey research: challenges and opportunities 1 (O-201)

Convenor Mr Arnaud Wijnant (CentERdata – Tilburg University)

We live in a rapidly changing world in which people using smartphones all the time, being on Facebook, tweet about what they like, a world of ‘internet of things’ in which more and more data are available. All these data could in potential be a new source of information for survey researchers. However, this implies another way in how we collect and analyse data, moreover how can these new sources of data help survey researchers?

Smartphones and tablets for example offer new opportunities for collecting ‘passive’ data which can provide insight into how individuals use smartphones, GPS information tells us more about the exact location of the respondent and can track their patterns of mobility. Pop-up questions which allow us to ask people at random intervals how they feel at that moment (Experience Sampling). Other options are to ask respondents to make photos or videos and to scan the barcodes of what they bought. Furthermore all these kinds of data can be combined (with traditional surveys) to give a full overview of the respondent’s behaviour and well-being.

Social media offer new ways of collecting information on people without asking questions. How can twitter and other social media help to improve surveys or give a deeper understanding in people’s opinions or behaviour?

In this session we want to examine best practices and new ways of collecting and analysing data that can complement survey research. We welcome contributions, but not limited to these, which report on the use of smartphones, social media and other new sources of data in their research design.


Occupations and survey research: methodological and substantive applications exploiting occupations as social contexts 1 (O-106)

Convenor Professor Christian Ebner (University of Cologne, Germany)
Coordinator 1Dr Daniela Rohrbach-schmidt (Federal Institute for Vocational Education and Training, Bonn, Germany)

The individual’s occupation belongs to the most frequently surveyed and most used background variables in social surveys. Occupational codes are regularly used as nominal units within fixed-effects approaches (economics), or they are recoded into different status measures or class schemes (sociology). More recent approaches describe occupations as “microclass” categories, which shape individual behavior and attitudes (e.g. Weeden/Grusky 2005). This view is also interesting from a methodological view, as it understands occupations as a contextual unit, in which individuals are nested and socialized.

Following this approach our session focuses on occupations as a higher-level unit of analysis in multi-level designs. The session is a good opportunity to reflect on:
- How the relevance of occupations as a social context can be justified / what are valuable concepts to understand and systemize the occupational level?
- How occupational characteristics (e.g. regulations, skill / job task requirements) help to explain social phenomena at the individual level?

Methodological papers might address issues related to multi-level techniques (hierarchical, non-hierarchical, cross-classified), levels of occupational aggregation and data linkage, (inter)national occupational classifications, and the comparability of results between regions or countries. Substantive papers might cover the usefulness of the occupational context for the understanding of e.g. attitudes and lifestyles, labor market outcomes or well-being. In particular, we are interested in the theoretical and empirical mechanisms (e.g. social closure (ibid.), technological change (Autor/Handel 2013)), which lead to the described outcomes at the individual level.

References:
Autor, David; Handel, Michael (2013). Putting Tasks to the Test: Human Capital, Job Tasks, and Wages. Journal of Labor Economics 31(2): S59-S96.
Weeden, Kim; Grusky, David (2005). The Case for a New Class Map. American Journal of Sociology 111(1): 141-212.


Open-ended questions in web panels and web surveys (HT-104)

Convenor Professor Matthias Schonlau (University of Waterloo)

Open-ended questions do not constrain respondents’ answer choices. Open-ended questions can clarify previous answers or the dreaded multiple choice category “other”. Web panels routinely include open-ended questions in the form of a final questions (“Do you have any other comment?”). Open-ended questions are well suited to web surveys and web panels because respondents’ type themselves; no transcription is required. We welcome all contributions related to open-ended questions in web surveys, web panels, and handheld survey devices.


Potential and Challenges of Cognitive Interviewing and Online Probing in a Cross-National Context (O-206)

Convenor Mr Andrew Johnson (Ipsos MORI)
Coordinator 1Ms Katarina Meitinger (GESIS)

A key consideration of cross-national surveys is that their questions possess functional equivalence, allowing for comparative analysis across people of differing cultural and linguistic backgrounds.

Cognitive interviewing plays an invaluable role in uncovering problems of non-equivalence and offers at the same time the possibility to identify the causes of non-equivalence. However, its application in a cross-national setting faces unique challenges, such as the need to have multiple interviewing teams, often speaking different languages and possessing varying levels of interviewing experience and training. Teams may also have more or less experience of analyzing cognitive interviewing findings, and may be better or worse at making the sometimes fine analytical distinctions between problems of functional equivalence, translation error or poor source question design.

Recently, the supplemental method of online probing has been developed that implements probing techniques in cross-national web surveys. It allows for a relatively inexpensive increase in sample size, probe standardization and a quantification of results (Behr et al. 2012) but faces its own challenges, such as mismatching answers or probe non-response.

For this session, we invite papers that address the topic of equivalence testing by making use of either cognitive interviewing or online probing. What can the different methods achieve and where do they face challenges? And most importantly: How can these challenges be resolved?

Papers are welcome on both substantive findings and on methodological challenges and considerations. This session also invites papers that can provide a helpful contribution to understanding how best to achieve a uniformity of approach in cross-country cognitive interviewing, with a focus on, but not restricted to:
• Interviewer training and briefing
• Interview protocols
• Collection, organization and analysis of cognitive interviewing data

Co-organizers: Tom Frere-Smith, Ipsos and Dorothée Behr, GESIS


Propensity score methods: methodological developments and innovative applications (HT-101)

Convenor Dr Bruno Arpino (Universitat Pompeu Fabra)

Methods, such as matching, weighting and stratification, based on the propensity score have been increasingly used in many fields for estimating causal effects in observational studies. Still a lot of methodological work needs to be done to identify optimal ways of specifying the propensity score model, analyzing covariates balance, treat missing data and measurement error, etc. The panel will focus on recent developments in propensity score methods that address one or more of these issues. Submissions regarding innovative use of propensity score methods in applied works are also welcome.


Sample composition in online studies (HT-102)

Convenor Mr Ulrich Krieger (German Internet Panel, SFB 884, University of Mannheim)

This session focusses on sample composition in internet based research.

As not every member of the population has access to the web, online studies are prone to coverage error and thus resulting in a selective sample. This is problematic when researchers want to draw inference on the population as a whole, online and offline sample members.

Papers in this session explore the effect on sample composition when this mode is being used. Also measures to counter the effects of data collection via the web are being discussed.


Surveying children and young people 3 (L-103)

Convenor Miss Emily Gilbert (Centre for Longitudinal Studies, Institute of Education)
Coordinator 1Ms Lisa Calderwood (Centre for Longitudinal Studies, Institute of Education)

Many large-scale surveys successfully collect a variety of different types of data from children and young people. However, there is relatively little methodological evidence in this area. Much of the literature relating to children and young people’s participation in research focuses on small-scale qualitative studies and tends to concentrate on ethical issues relating to the rights of children and young people in research. This session will cover experiences of including children and young people in surveys, and related survey design issues. The session aims to explore a variety of methodological issues around surveying children and young people. Submissions are particularly welcomed on:
- designing questionnaires for children and young people, including question testing methods
- collecting sensitive data from children and young people, including methods for ensuring privacy and encouraging accurate reporting
- collecting different types of data from children and young people, including physical measurements, cognitive assessments, biological samples and time use data
- using different methods of data collection, including the use of innovative technology such as the web and mobile phones
- inclusivity in data collection methods, including facilitating the participation of young people with lower literacy levels
- assessing the reliability and validity of young people’s self-reports
- preventing non-response by engaging young people in research, including designing survey materials to appeal to young people and using new technology and digital media for participant engagement
- ethical issues in involving children and young people in surveys, including gaining informed consent and protecting children’s rights and well-being


Technical Problems and Solutions for Record Linkage and Big Data 1 (HT-103)

Convenor Dr Manfred Antoni (Institute for Employment Research (IAB))
Coordinator 1Mr Stefan Bender (Institute for Employment Research (IAB))
Coordinator 2Professor Rainer Schnell (University of Duisburg-Essen)

The scope of the session includes technical issues of linkage, handling large administrative databases or big data (for example, blocking strategies) and problems caused by incomplete identifiers. Furthermore, techniques and problems of privacy preserving record linkage and secure access to linked datasets will be discussed. Finally, new algorithms and software for record-linkage applications for large datasets will be covered.

We invite presentations on:
• Handling missing and messy identifiers
• Blocking techniques
• Privacy Preserving Record Linkage
• Access to linked datasets
• Algorithms and Software


Using Surveys to Study the Environment (N-131)

Convenor Dr Malcolm Fairbrother (University of Bristol)
Coordinator 1Dr Kerry Ard (Ohio State University)

Effective public policies and regulations have begun to mitigate many environmental problems globally, but many problems remain severe (e.g., urban air pollution) or are getting worse (greenhouse gas emissions, species extinctions). There is an urgent need for research on solutions to such problems, and in this regard surveys have much to offer. Existing research has used health surveys to show that exposure to environmental toxins is an important determinant of human health outcomes. Political researchers have shown how public opinion has often shaped key environmental policy outcomes. Building on previous studies of these kinds, this session welcomes papers related to survey research on environmental topics broadly defined. Papers may be either substantive or methodological. Substantively, papers should address topics including but not limited to: the measurement of environmentally consequential behaviours and lifestyles; public concern about environmental problems; political attitudes relevant to environmental protection; or the impacts of pollution on human health and well-being (including stress and mental health). What are the correlates of less environmentally damaging behaviours, greater environmental concern, more pro-environmental attitudes, or greater exposure to environmental toxins? Papers may use datasets that are comparative or single-nation, cross-sectional or longitudinal, but should all make an important contribution to some substantive field of research relevant to the natural environment. For example, how does exposure to environmental toxins vary across different demographic groups, and how is such exposure changing over time? Under what conditions do people support (or oppose) measures for environmental protection? (What kinds of people, and what kinds of protections?) Methodologically, we are interested in innovations such as survey experiments, new or improved measures, new analytical techniques appropriate for data types of particular relevance to the environment, and innovative survey modes and forms of data linkage.


Comparative Welfare Research: Actors, Arenas, Attitudes 1 (N-132)

Convenor Dr Joakim Kulin (Department of Sociology, Stockholm University)
Coordinator 1Dr Jan Mewes (School of Humanities, Education and Social Sciences, Örebro University)

This session invites papers from different areas of comparative welfare research, with a particular interest in studies making use of cross-national survey data. Our interest goes beyond the by now established field of comparative welfare state research as it invites papers that focus on a multitude of actors and arenas related to public welfare and the production of collective goods. In this respect, we invite papers that address the configuration of, and public attitudes towards, state and market based welfare institutions. A broad range of paper submissions is encouraged, including a variety of methods and theoretical perspectives. In particular, we seek substantive applications in the broader field of welfare research that use rigorous and state-of-the-art methods. For instance, cross-national welfare research has for a long time been dominated by operationalizations that can be seriously questioned in terms of validity and equivalence (e.g., additive indices). Therefore, we welcome paper submissions that take seriously the issues of measurement quality and the cross-national comparability of measurements. Additionally, we also encourage submissions that exploit the full potential of survey data, such as for example vignette studies and survey experiments.


Data Collection Management: Monitoring Bias in a Total Survey Error Context (O-202)

Convenor Mr Brad Edwards (Westat)

In the total survey error paradigm, nonsampling errors and their relationship to cost have been very difficult to quantify, especially in real time. This is especially vexing in surveys conducted by interviewers, because of their large labor costs. Recent advances in paradata processing and analysis offer an opportunity to address this problem in survey operations. (Kreuter 2013) For example, CARI data selected with known probabilities from a pretest could be used to produce estimates of questionnaire (specification) error, to make improvements to address the design problems, and to monitor error levels after changes are implemented in the main data collection phase of face-to-face or telephone surveys. (Hicks, Edwards, Tourangeau, et al. 2010). The additional cost of CARI coding and analysis could reduce the resources available to complete more interviews, but result in a net reduction in bias.
Another example: GIS data could detect likely interview falsification on 100% of the cases completed on face-to-face surveys, at much lower cost than other techniques. GPS data from face-to-face surveys can detect falsification as it happens, thereby improving quality and saving costs that could be directed elsewhere. The quality improvement could be estimated by comparing the level of falsification detected with GPS compared to the level detected by more traditional methods (e.g., mail return forms, telephone and in-person re-interviews, CARI coding). Data collection savings from this innovation could be estimated by comparing the GPS costs with the costs of detecting and remediating falsifiers using traditional methods..
This session will include presentations on recent developments in CARI, GPS, mobile technology, and call record data and on studies that detect bias associated with various data collection activities, informed by the TSE paradigm.


Dealing with content validity in cross-cultural research. Methodological challenges and innovative approaches (O-101)

Convenor Dr Wolfgang Aschauer (University of Salzburg)
Coordinator 1Professor Martin Weichbold (University of Salzburg)

The main research aim of cross-national survey instruments (such as the European Social Survey, the ISSP or the World Value Survey) is to achieve comparable results and the key term to reach this goal is “equivalence”, more exactly: “functional equivalence”. Regarding certain aspects (e.g. sampling or translation) considerable progress has been made during the last years but in certain areas there is still a clear need for further research. One particular area is the task to achieve content validity of the major research themes in cross-national research. There is already awareness of certain biases with regards to latent constructs, indices and measurement concepts, but the challenges how to capture the various aspects of a specific construct in certain countries remain often unsolved. In many applied projects we can still observe the problematic strategy of an inconsiderate use of Western-based approaches which claim universality. On the other hand several researchers start to apply rather strict tests to achieve construct equivalence before defining and searching for the constituent parts of the constructs in specific countries. Excluding indicators which do not fit to the established models which claim to be culturally invariant can thus go hand in hand with a decreasing validity of the measurement in certain countries. Therefore construct equivalence and content validity are two different aspects and should be addressed separately in methodological research.

In the proposed session we especially look for contributions focusing on the validity of the measurement of certain (culturally sensitive) constructs. Survey researchers who are active in various research fields are highly welcome to present methodological groundwork on the proposed issues, to present their own strategies to deal with content validity in ongoing research projects or to discuss existing, alternative or innovative approaches of equivalence testing keeping certain validity constraints in mind.


Estimating effects of modes and mixed modes designs 1 (HT-105)

Convenor Mr Alexandru Cernat (Institute for Social and Economic Research, University of Essex)

Traditional approaches to data collection in the social sciences (i.e., face to face and telephone surveys) are becoming more expensive. At the same time cheaper approaches, such as web surveys, lack traditional sampling frames. This has led to a surge in data collection designs that aim to combine the strength of each mode into a single survey. In this context, accumulating evidence that informs design decision in mixed modes surveys is essential.

This session will contribute to this debate by tackling some important topics such as:
- Is the effect of social desirability moderated by mode?
- How do self-administered strategies (e.g., paper and web) differ in data quality?
- Are traditional scales (like those measuring personality, depression, cognitive ability) equivalent across modes?
- How does selection/non-response bias differ across modes?
- Does the use of mixed mode data impact substantive results?
- How does research on mixed mode integrate in the Total Survey Error framework?
- How to prevent mode effects through design?


Measuring gender role attitudes (N-131)

Convenor Ms Jessica Walter (GESIS - Leibniz-Institute for the Social Sciences)
Coordinator 1Mr Christof Wolf (GESIS - Leibniz-Institute for the Social Sciences)

Many studies analyze gender role attitudes, in particular how they change over time or how they differ across countries. These studies depend on the quality of measures provided in surveys. In most international or national omnibus surveys based on representative samples, indicators of gender role attitudes are part of a complex questionnaire. Consequently, surveys mainly use short measures of gender role attitudes which were usually developed in the1970s and 1980s.
For analyses over time or/and across countries the equivalence of measures of gender role attitudes is crucial. Measures of gender role attitudes should not change over time and should not depend on the cultural context. Social changes such as a differentiation of family patterns and changes in (female) labor force participation and education challenge the assumption that the measures are equivalent over time. Based on these changes we suggest that the measures of gender role attitudes need to be revisited and updated. By doing so, different cultural contexts, which may limit the equivalence of measures of gender role attitudes across countries, also come into focus.
The session aims at discussing how equivalence of measures of gender role attitudes over time and across countries can be ensured and how these measures can be adjusted to social changes. The focus of the discussion is on adjustments of measures of gender role attitudes which improve the equivalence of measures and on best practices for an implementation of improved measures in cross-cultural or longitudinal surveys.
We welcome all papers which deal with the advancement of measures of gender role attitudes or use new measures of gender role attitudes with focus on analyses over time and/or across countries.


Mixing Survey and Qualitative Data 2 (L-102)

Convenor Professor Nina Baur (Technische Universität Berlin)
Coordinator 1Dr Leila Akremi (Technische Universität Berlin)
Coordinator 2Ms Melanie Wenzel (Technische Universität Berlin)

The session invites papers that discuss how to mix survey data with qualitative data, e.g. qualitative interviews, ethnography, video analysis etc. Presenters are specifically asked to discuss what methodlogical problems they faced and how they handled them.


Occupations and survey research: methodological and substantive applications exploiting occupations as social contexts 2 (O-106)

Convenor Professor Christian Ebner (University of Cologne, Germany)
Coordinator 1Dr Daniela Rohrbach-schmidt (Federal Institute for Vocational Education and Training, Bonn, Germany)

The individual’s occupation belongs to the most frequently surveyed and most used background variables in social surveys. Occupational codes are regularly used as nominal units within fixed-effects approaches (economics), or they are recoded into different status measures or class schemes (sociology). More recent approaches describe occupations as “microclass” categories, which shape individual behavior and attitudes (e.g. Weeden/Grusky 2005). This view is also interesting from a methodological view, as it understands occupations as a contextual unit, in which individuals are nested and socialized.

Following this approach our session focuses on occupations as a higher-level unit of analysis in multi-level designs. The session is a good opportunity to reflect on:
- How the relevance of occupations as a social context can be justified / what are valuable concepts to understand and systemize the occupational level?
- How occupational characteristics (e.g. regulations, skill / job task requirements) help to explain social phenomena at the individual level?

Methodological papers might address issues related to multi-level techniques (hierarchical, non-hierarchical, cross-classified), levels of occupational aggregation and data linkage, (inter)national occupational classifications, and the comparability of results between regions or countries. Substantive papers might cover the usefulness of the occupational context for the understanding of e.g. attitudes and lifestyles, labor market outcomes or well-being. In particular, we are interested in the theoretical and empirical mechanisms (e.g. social closure (ibid.), technological change (Autor/Handel 2013)), which lead to the described outcomes at the individual level.

References:
Autor, David; Handel, Michael (2013). Putting Tasks to the Test: Human Capital, Job Tasks, and Wages. Journal of Labor Economics 31(2): S59-S96.
Weeden, Kim; Grusky, David (2005). The Case for a New Class Map. American Journal of Sociology 111(1): 141-212.


Representativeness of Surveys Using Internet-based Data Collection (HT-102)

Convenor Professor Michael Bosnjak (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 1Mr Ulrich Krieger (University of Mannheim)
Coordinator 2Dr Tobias Enderle (GESIS - Leibniz Institute for the Social Sciences)

Statistical theory is essentially based on random probability samples. However, Web surveys making use of convenience samples and volunteer access panels, where respondents self-select themselves into the sample, still dominate the landscape. Such recruitment strategies are attractive due to their low costs. Yet, recent years have seen increasing debates surrounding their quality in terms of representativeness. As a consequence, researchers across several countries are working towards Internet and mixed-mode panels based on probability samples.

The overall aim of this session is to provide a platform to present and to discuss recent research on the representativeness of surveys making use of Internet-based data collection modes (i.e., Web surveys, self-administered mobile surveys). The scope of this sessions encompasses both cross-sectional as well as panel-based surveys using Internet surveys as the sole data collection mode, or as one mode within a mixed mode context. Proposals may include, but are not limited to, the following topics:

* Representativeness concepts and corresponding indicators applicable to Internet-based and mixed-mode surveys
* Representativeness of Internet-based surveys and mixed-mode surveys of the general population compared to well-established modes
* Sample recruitment and refreshment strategies aimed at ensuring representativeness in (Internet-based and mixed-mode) access panels
* Effectiveness of various survey implementation measures and procedures aimed at ensuring representativeness (e.g., effectiveness of panel maintenance strategies, incentives, non-responder conversion, etc.)


Robust Methods in Survey Design and Analysis with Applications (HT-101)

Convenor Dr Marco Geraci (University of South Carolina)
Coordinator 1Dr James Hardin (University of South Carolina)
Coordinator 2Dr Andrew Ortaglia (University of South Carolina)

The violation of the assumptions that underlie parametric statistical methods is potentially a serious issue when drawing inferences about a population. Resulting bias in the estimates may lead to incorrect conclusions. Typical problems include, but are not limited to, the presence of outliers, untenable normality assumptions, and model misspecification.

This session aims at showcasing recent developments in robust methods for survey design and survey data analysis with emphasis on applications. Submissions on topics such as semi- and non-parametric modelling, estimation of distribution functions and quantiles, variance estimation and methods for missing data are particularly welcome. The presentations will illustrate the application of robust methods to studies in the life, social and natural sciences. Examples on the usage of related statistical software are also encouraged.


Surveying children and young people 4 (L-103)

Convenor Miss Emily Gilbert (Centre for Longitudinal Studies, Institute of Education)
Coordinator 1Ms Lisa Calderwood (Centre for Longitudinal Studies, Institute of Education)

Many large-scale surveys successfully collect a variety of different types of data from children and young people. However, there is relatively little methodological evidence in this area. Much of the literature relating to children and young people’s participation in research focuses on small-scale qualitative studies and tends to concentrate on ethical issues relating to the rights of children and young people in research. This session will cover experiences of including children and young people in surveys, and related survey design issues. The session aims to explore a variety of methodological issues around surveying children and young people. Submissions are particularly welcomed on:
- designing questionnaires for children and young people, including question testing methods
- collecting sensitive data from children and young people, including methods for ensuring privacy and encouraging accurate reporting
- collecting different types of data from children and young people, including physical measurements, cognitive assessments, biological samples and time use data
- using different methods of data collection, including the use of innovative technology such as the web and mobile phones
- inclusivity in data collection methods, including facilitating the participation of young people with lower literacy levels
- assessing the reliability and validity of young people’s self-reports
- preventing non-response by engaging young people in research, including designing survey materials to appeal to young people and using new technology and digital media for participant engagement
- ethical issues in involving children and young people in surveys, including gaining informed consent and protecting children’s rights and well-being


Technical Problems and Solutions for Record Linkage and Big Data 2 (HT-103)

Convenor Dr Manfred Antoni (Institute for Employment Research (IAB))
Coordinator 1Mr Stefan Bender (Institute for Employment Research (IAB))
Coordinator 2Professor Rainer Schnell (University of Duisburg-Essen)

The scope of the session includes technical issues of linkage, handling large administrative databases or big data (for example, blocking strategies) and problems caused by incomplete identifiers. Furthermore, techniques and problems of privacy preserving record linkage and secure access to linked datasets will be discussed. Finally, new algorithms and software for record-linkage applications for large datasets will be covered.

We invite presentations on:
• Handling missing and messy identifiers
• Blocking techniques
• Privacy Preserving Record Linkage
• Access to linked datasets
• Algorithms and Software


The Nimble Survey Methodology in Addressing Humanitarian Emergencies 1 (HT-104)

Convenor Dr Asaph Young Chun (US Census Bureau and ASA Statistics Without Borders)
Coordinator 1Dr Fritz Scheuren (NORC at the University of Chicago)
Coordinator 2Professor James Cochran (University of Alabama)

Could survey methodology be agile enough to help resolve humanitarian crises that have fast and lasting impacts on many people's lives? This session is devoted to discussing survey methodology that has played a vital role in efforts to resolve acute humanitarian crises affecting the disadvantaged people disproportionately.

The papers relevant to this session include, but are not limited to the following: health surveys of the disadvantaged people, such as children, women and disabled population in hard-to-access countries; survey studies leveraging SNS tools for the humanitarian disaster response; and agile surveys supplemented by administrative records and/or big data addressing humanitarian interventions. We are open to accepting case studies that leveraged interdisciplinary survey methodology to address human right issues in developing countries. Research papers in this session use survey methodology and interdisciplinary thinking to assist Non-Governmental Organizations and/or UN agencies in addressing current humanitarian crises or human rights.

Papers encouraged to submit include innovative studies demonstrating how survey research has led to nimble policy decisions that help save many people's lives and/or improve quality of life of the disadvantaged people in developing countries. Submissions of interests are agile survey research that promoted synergy of academics, NGOs and UN agencies as well as governmental agencies to help develop humanitarian interventions. This session should be of interest to most ESRA participants and to those who are involved or wish to be involved with survey methodology applied to humanitarian efforts or human rights across the globe.


What does it mean to produce equivalent questionnaire translations 1? (O-206)

Convenor Dr Dorothée Behr (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 1Dr Alisú Schoua-glusberg (Research Support Services Inc.)
Coordinator 2Ms Brita Dorer (GESIS - Leibniz Institute for the Social Sciences)

Equivalent data in cross-cultural and cross-national surveys is the precondition for any meaningful comparison across countries or cultures. Equivalence is a complex concept, though. Johnson (1998) lists over 50 different equivalence definitions from the social sciences, psychology and related fields that may broadly be classified into interpretive and procedural equivalence. The field of translation studies equally struggles with a multitude of approaches and definitions (Kenny, 1998), which specify, for instance, the rank of equivalence (e.g., word or textual level) or the type of equivalence (denotative, pragmatic, etc.) that can be obtained.

In this session, we will look into what it means to produce equivalent questionnaire translations. Key questions in this regard are: What needs to be kept equivalent and what needs to change in order to produce questionnaire translations that work as intended? What guidance can be given to translators of questionnaires in cross-national studies?

Presenters are invited to cover any of the following topics: (1) equivalence of form vs. equivalence of effect; (2) face-value-equivalence vs. perceived meaning; (3) the role of culture-specific discourse conventions (e.g., directness, politeness; theme-rheme); (4) questionnaire design principles (usually developed on the basis of the English language) and their challenges for translation; (5) challenges for particular language combinations; (6) methods to address equivalence: interplay between statistical assessment and expert judgment, split-ballot, mixed-method, rating tasks (for response scales, for instance), corpus linguistics. Presentations are encouraged to further our knowledge on “changes” in the translation that may be necessary in order to produce translations that pave the way for comparable data.


Comparative Welfare Research: Actors, Arenas, Attitudes 2 (N-132)

Convenor Dr Joakim Kulin (Department of Sociology, Stockholm University)
Coordinator 1Dr Jan Mewes (School of Humanities, Education and Social Sciences, Örebro University)

This session invites papers from different areas of comparative welfare research, with a particular interest in studies making use of cross-national survey data. Our interest goes beyond the by now established field of comparative welfare state research as it invites papers that focus on a multitude of actors and arenas related to public welfare and the production of collective goods. In this respect, we invite papers that address the configuration of, and public attitudes towards, state and market based welfare institutions. A broad range of paper submissions is encouraged, including a variety of methods and theoretical perspectives. In particular, we seek substantive applications in the broader field of welfare research that use rigorous and state-of-the-art methods. For instance, cross-national welfare research has for a long time been dominated by operationalizations that can be seriously questioned in terms of validity and equivalence (e.g., additive indices). Therefore, we welcome paper submissions that take seriously the issues of measurement quality and the cross-national comparability of measurements. Additionally, we also encourage submissions that exploit the full potential of survey data, such as for example vignette studies and survey experiments.


Health inequalities between health survey participants and non-participants (HT-102)

Convenor Dr Hanna Tolonen (National Institute for Health and Welfare, Helsinki, Finland)

Health surveys, especially health examination surveys where physical measurements are conducted and biological samples are collected, are important data sources about health of the population. This information can be used for evidence-based policy making, planning and evaluation of prevention programmes as well as for research.

The participation rates of health surveys have declined in past decades similarly to other surveys. There is also evidence that health and risk factor profiles of survey participants and non-participants differ. Previous studies have shown that mortality of non-participants is twice as high as that of participants, and for example smoking related mortality is three times higher among non-participants. These observed health inequalities between health survey participants and non-participants imply that survey non-participants have more diseases and worse health behaviors, such as smoking, than participants. Better understanding of these differences is needed, to ensure that our interpretation of survey results for evidence-based policy making and research are accurate.

The aim of this session is to present research findings about the differences in health and risk factor profiles of survey participants and non-participants, with special focus on health surveys.


Marrying survey methodology with survey management: Minimizing the Total Survey Error (TSE) with limited resources during fieldwork (O-202)

Convenor Dr Frederic Malter (Max-Planck-Society)

The key goal of any survey is to deliver statistics with minimal errors that facilitate correct conclusions about the target population. It is easy to understand how applying the TSE can be a useful concept for minimizing the risk of flawed survey statistics at the “early life” of a survey, i.e. the design stage (e.g. designing survey items or scales with good psychometric properties) or the “late life” stage, i.e. the post-production phase such as applying post-stratification weighting to account for unit non-response. It is much less clear, however, how to allocate the limited resources at a survey’s “mid-life” stage, i.e. the fieldwork phase, to the various components of the total survey error. For example, how do surveys allocate resources to minimize measurement errors arising from non-standardized interviewing? A practical example is interviewers’ shortcutting question texts or introduction texts that will create non-standardized interviewing. Another example may be issues arising from sampling errors: how do surveys minimize the risk of unit nonresponse with their limited resources?
The goal of this session is to bring survey managers and survey methodologists together to discuss solutions to the problem of allocating limited resources (training, survey managers’ time, incentives for interviewers etc.) to the various components of the TSE while fieldwork is still ongoing. Ideally, the session will yield ideas on important “set screws” and how to get the biggest bang along the two major lines of intervening: training/managing interviewers and providing monetary or non-monetary incentives.
Any contribution applying the TSE ex-ante to fieldwork management or contributions of survey studies retro-fitting principles of TSE to their current fieldwork management are welcome. Ideally, submission will briefly lay out how the input side (e.g. incentives) is mapped onto the output.


Multilevel Models for the Analysis of Comparative (Longitudinal) Survey Data 3 (L-101)

Convenor Dr Alexander Schmidt-catran (Institute of Sociology and Social Psychology, University of Cologne)
Coordinator 1Professor Bart Meuleman (Centre for Sociological Research, University of Leuven)

Multilevel models have become predominant in analyses of comparative survey datasets, where respondents are clustered in higher-level units like countries or regions. Such models have also long been fitted to longitudinal data, where repeated observations are clustered within units. Additionally, researchers are fitting multilevel models to data that are clustered both ways, such as multiple waves of surveys whose respondents are nested in countries or regions each observed multiple times. These comparative longitudinal survey datasets should be useful resources for studies of social change in the broadest sense, and for drawing inferences previously based on only cross-sectional analyses. This session welcomes papers using multilevel models for the analysis of cross-sectional data, longitudinal data and, in particular, data that is clustered both ways. Papers might address recent methodological advances; present illuminating or innovative applications in some field of the social sciences; and/or discuss limitations and challenges that remain.


Occupations and survey research: methodological and substantive applications exploiting occupations as social contexts 3 (O-106)

Convenor Professor Christian Ebner (University of Cologne, Germany)
Coordinator 1Dr Daniela Rohrbach-schmidt (Federal Institute for Vocational Education and Training, Bonn, Germany)

The individual’s occupation belongs to the most frequently surveyed and most used background variables in social surveys. Occupational codes are regularly used as nominal units within fixed-effects approaches (economics), or they are recoded into different status measures or class schemes (sociology). More recent approaches describe occupations as “microclass” categories, which shape individual behavior and attitudes (e.g. Weeden/Grusky 2005). This view is also interesting from a methodological view, as it understands occupations as a contextual unit, in which individuals are nested and socialized.

Following this approach our session focuses on occupations as a higher-level unit of analysis in multi-level designs. The session is a good opportunity to reflect on:
- How the relevance of occupations as a social context can be justified / what are valuable concepts to understand and systemize the occupational level?
- How occupational characteristics (e.g. regulations, skill / job task requirements) help to explain social phenomena at the individual level?

Methodological papers might address issues related to multi-level techniques (hierarchical, non-hierarchical, cross-classified), levels of occupational aggregation and data linkage, (inter)national occupational classifications, and the comparability of results between regions or countries. Substantive papers might cover the usefulness of the occupational context for the understanding of e.g. attitudes and lifestyles, labor market outcomes or well-being. In particular, we are interested in the theoretical and empirical mechanisms (e.g. social closure (ibid.), technological change (Autor/Handel 2013)), which lead to the described outcomes at the individual level.

References:
Autor, David; Handel, Michael (2013). Putting Tasks to the Test: Human Capital, Job Tasks, and Wages. Journal of Labor Economics 31(2): S59-S96.
Weeden, Kim; Grusky, David (2005). The Case for a New Class Map. American Journal of Sociology 111(1): 141-212.


Practical solutions for mixed mode survey users and producers (HT-105)

Convenor Mrs Michèle Ernst Stähli (FORS, FORS, Swiss Centre of Expertise in the Social Sciences)
Coordinator 1Mrs Caroline Roberts (Institut des sciences sociales, University of Lausanne)

Mixed mode surveys have been gaining popularity over the course of the past decade. Many academically led and government-funded studies have been exploring such survey designs whereas survey organisations in some countries now routinely offer clients mixed mode survey designs as a way to improve population coverage and reduce survey costs. In response to these developments, the methodological literature exploring the advantages and disadvantages of mixed mode surveys has burgeoned, with a growing number of studies tackling the thorny issue of how to disentangle so-called ‘mode effects’ (differential measurement errors between modes) from selection effects. This research has highlighted the considerable analytic burden mixed mode data place on methodologists interested in measuring and potentially correcting for confounded survey errors, as well as on substantive researchers who analyze mixed mode data. Yet, there is still a relative lack of guidance available for designers and users of mixed mode data about whether mode effects matter enough to preclude the use of such data collection designs, or to warrant the use of potentially cumbersome analytic methods to control the potential impact of measurement differences on substantive research conclusions.
How should data providers and data users handle mixed mode data? What procedures need to be undertaken when analysts start to use the data? What thresholds should we set to decide whether measurement differences between modes are important enough to warrant special measures at the analysis stage? What preventative measures have to be taken in order to avoid a misuse of mixed mode data?
For this session, we are particularly interested in contributions that consider, in a pragmatic way, the challenges of using mixed mode data, and offer practical solutions, either for survey designers deciding whether to mix modes, or for data users approaching their analyses.


The Challenges of Survey and Administrative Data Linkage (HT-103)

Convenor Dr Tarek Mostafa (UCL Institute of Education)

Surveys face significant challenges due to the rise in survey costs, attrition over time, and non-coverage of the target population. All these challenges have the potential of damaging the quality of the collected data. One method of reducing the costs of data collection and improving quality is to link selected individual administrative information to the survey record. Administrative data linkage leads to shorter interviews, less respondent burden and an overall reduction in costs, in addition to the gain of valuable information on respondents. However, access to administrative records will suffer from non-consent whenever respondents refuse permission to link their records, and non-linkage when it is impossible to link the records even though consent was given.

This session provides a series of original investigations on consent and linkage of survey and administrative data. The first two papers deal with consent in the context of longitudinal and panel surveys. The third paper explores consent to administrative data linkage in the context of a sequential mixed-mode survey. The fourth examines the success in linking housing data from survey, administrative, and commercial sources, and finally the fifth presents evidence from a feasibility study on linking health data from three different sources.


The interplay of conceptual and measurement validity in cross-nation analysis (O-101)

Convenor Professor Jaak Billiet (CeSO - KU Leuven)

There is a long-standing tradition of cross-nation research, especially in comparative analysis in which political systems are analysed as cases or used as context. Social researchers believe that the context affects individual characteristics, attitudes, choices and behaviour. The nature of the research questions that ask for comparative quantitative analysis has been drastically changed due to the increasing availability of comparable micro data collected in many countries, and the development in methodology. Notwithstanding the advancements made, cross-nation research still confronts considerable scientific challenges, both in terms of methodology and the underlying theoretical assumptions. In recent years, a attention is paid to the challenges of measurement validity in broad sense (non-response bias and measurement equivalence) and to statistical analysis of hierarchical models. Less attention has been paid to the assumptions behind conceptualization and design aspects of relation in hierarchical models.
In this section we hope to discuss papers in which attention is paid to the assumptions made when lower and higher level variables are combined into explanatory multi-level models. We welcome papers in which attention is paid to the so called micro-macro link, the designs used, and the validity of operationalization and inferences. Reflections based at empirical examples of research are especially welcomed.

Background paper: Billiet, J., Meuleman, B. & Davidov, E. (2015). Some methodological challenges of cross-national social Research: conceptual and measurement validity. In Pawel B. Sztabinski, Henryk Domanski, and Franek Sztabinski (eds.) Hopes and Anxieties. Six Waves of the European Social Survey. Frankfurt am Main: Peter Lang (in press: expected April 2015)



The Nimble Survey Methodology in Addressing Humanitarian Emergencies 2 (HT-104)

Convenor Dr Asaph Young Chun (US Census Bureau and ASA Statistics Without Borders)
Coordinator 1Dr Fritz Scheuren (NORC at the University of Chicago)
Coordinator 2Professor James Cochran (University of Alabama)

Could survey methodology be agile enough to help resolve humanitarian crises that have fast and lasting impacts on many people's lives? This session is devoted to discussing survey methodology that has played a vital role in efforts to resolve acute humanitarian crises affecting the disadvantaged people disproportionately.

The papers relevant to this session include, but are not limited to the following: health surveys of the disadvantaged people, such as children, women and disabled population in hard-to-access countries; survey studies leveraging SNS tools for the humanitarian disaster response; and agile surveys supplemented by administrative records and/or big data addressing humanitarian interventions. We are open to accepting case studies that leveraged interdisciplinary survey methodology to address human right issues in developing countries. Research papers in this session use survey methodology and interdisciplinary thinking to assist Non-Governmental Organizations and/or UN agencies in addressing current humanitarian crises or human rights.

Papers encouraged to submit include innovative studies demonstrating how survey research has led to nimble policy decisions that help save many people's lives and/or improve quality of life of the disadvantaged people in developing countries. Submissions of interests are agile survey research that promoted synergy of academics, NGOs and UN agencies as well as governmental agencies to help develop humanitarian interventions. This session should be of interest to most ESRA participants and to those who are involved or wish to be involved with survey methodology applied to humanitarian efforts or human rights across the globe.


What does it mean to produce equivalent questionnaire translations 2? (O-206)

Convenor Dr Dorothée Behr (GESIS - Leibniz Institute for the Social Sciences)
Coordinator 1Dr Alisú Schoua-glusberg (Research Support Services Inc.)
Coordinator 2Ms Brita Dorer (GESIS - Leibniz Institute for the Social Sciences)

Equivalent data in cross-cultural and cross-national surveys is the precondition for any meaningful comparison across countries or cultures. Equivalence is a complex concept, though. Johnson (1998) lists over 50 different equivalence definitions from the social sciences, psychology and related fields that may broadly be classified into interpretive and procedural equivalence. The field of translation studies equally struggles with a multitude of approaches and definitions (Kenny, 1998), which specify, for instance, the rank of equivalence (e.g., word or textual level) or the type of equivalence (denotative, pragmatic, etc.) that can be obtained.

In this session, we will look into what it means to produce equivalent questionnaire translations. Key questions in this regard are: What needs to be kept equivalent and what needs to change in order to produce questionnaire translations that work as intended? What guidance can be given to translators of questionnaires in cross-national studies?

Presenters are invited to cover any of the following topics: (1) equivalence of form vs. equivalence of effect; (2) face-value-equivalence vs. perceived meaning; (3) the role of culture-specific discourse conventions (e.g., directness, politeness; theme-rheme); (4) questionnaire design principles (usually developed on the basis of the English language) and their challenges for translation; (5) challenges for particular language combinations; (6) methods to address equivalence: interplay between statistical assessment and expert judgment, split-ballot, mixed-method, rating tasks (for response scales, for instance), corpus linguistics. Presentations are encouraged to further our knowledge on “changes” in the translation that may be necessary in order to produce translations that pave the way for comparable data.


When do social media data align with survey responses and administrative data? (O-201)

Convenor Professor Michael Schober (New School for Social Research)
Coordinator 1Professor Frederick Conrad (University of Michigan)

Demonstrations that analyses of social media content can align with measurement from sample surveys or from administrative data (like unemployment insurance claims) have raised the question of whether survey research can be supplemented or even replaced with less costly and burdensome data mining of already-existing or “found” social media content. But just how trustworthy such measurement can be—say, to replace official statistics—is unknown. New conversations between survey methodologists and data scientists are needed to understand the potential points of alignment and non-alignment, given different starting assumptions and analytic traditions on, for example, the extent to which adequate social measurement requires representative samples drawn from frames that fully cover the population.

What is needed are principles and hypotheses for understanding when and why alignment between social media analyses and survey responses or administrative data should and should not be found. Empirically, demonstrations that social media data can predict survey responses do not always replicate. Much more needs to be understood about the effects of the many potentially relevant factors: the range of survey topics and domains, different methods for mining the social media content, different algorithms for converting social media content
into quantifiable data, and different techniques for measuring alignment.

This panel will present empirical work that advances the conversation about (a) when analyses of social media content might provide estimates accurate enough to be used as reliable social measures or published as official statistics—and when they might not, (b) how self-report in surveys and analyses of social media content might complement and supplement each other, and (c) what should inform decisions about which methods to use for which purposes.