ESRA 2013 Sessions

Data Management and Data Analysis in Quantitative Historical Social Research Dr Ronald Gebauer
Today, historical social research no longer is entirely restricted to the study and analysis of ususal historiographic sources, such as written records, manuscripts, or collections of chronological treatises. Currently, one can notice a kind of revolution: Many of these collections had or have been already transfered or copied to electronic media (CD or DVD) or will be, sooner or later. Besides, some historical data of more recent origin had been already collected in order to analyze them electronically. All these types of data have in common that they are ready or almost ready to be analyzed by applying advanced empirical research techniques and that their number is increasing day by day.
This panel is dedicated to the discussion of the analysis of historical data and its major methodological and technical problems. First, this will comprise issues concerning the process of data mining, the transfer of these data to electronic media, and their usage for empirical research in the contemporary Social Sciences and Humanities such as handling shifting validity and bias, detecting and repairing miscoded and missing data, as well as the optimal preparation for computer assisted analysis. Second, a further emphasis will be on strategies of data analysis focussed on historical social structure and historical social change. Third, in the case of more recent data, possibilities of data linking to contemporary data in order to complete longitudinal data such as biographies and other event histories will be discussed. Please submit your paper abstracts to Ronald Gebauer and Axel Salheiser, Institute of Sociology, University of Jena, Germany, ronald.gebauer@uni-jena.de or axel.salheiser@uni-jena.de.



Hierarchical data analysis with few upper level units: Solutions and applications beyond multi-level modelingDr Celine Teney
This panel addresses the problem of linking nested, "many-to-few" data while retaining important information about variation at all levels. To clarify further, one problem of traditional multilevel modeling techniques is that such models require a sufficiently large number of observations on the higher levels. However, it is often the case that interesting phenomenon occur where upper level observations are limited to numbers below common thresholds acceptable to draw inferences in traditional multilevel modeling. At the same time, the number of higher level units is too large to apply classical comparative case study designs. For instance, when attempting to link MPs' positions or behavior to party characteristics, scholars often face a problem that survey or roll-call data gives us sufficiently large number of observations for the individual level, but we are limited to few observations at the party level. The same is true for mass surveys conducted only a couple of times in a country, for example the ESS or the World Values Survey. Another up-to-date example would be the analysis of cross-national differences in citizens´ positions toward the EU in countries that benefited from the European rescue package.
Therefore, this type of many-to-few data linking poses a unique set of problems to researchers. Besides inappropriate multilevel modeling techniques, many of the proposed solutions to such problems like clustering or using country dummies do not or only in a very limited way allow researchers to explain variation in both the upper and lower level units--an often important point for theory testing. Our panel invites papers of both methodological and substantive nature which develop and explore innovative ways to overcome problems associated with such many-to-few, nested models while still seeking to explore patterns of variation at all levels.


Linking Survey and Administrative Records: Processes and selectivities of consent 1Ms Julie Korbmacher
Researchers are invited to submit presentation proposals at the session "Linking Survey and Administrative Records: Processes and selectivities of consent" at the European Survey Research Association conference, July, 15-19, 2013 in Ljubljana.

The number of studies linking survey and administrative records is still increasing in the social sciences. There are two ways how to link data, with different implications. In statistical or propensity score matching sample units from a survey are matched to "similar" (in a statistical sense) units in the administrative records. The other way is to link the two data sources directly which requires respondents' consent. The latter approach is usually thought to be more promising, but the fact the respondents' consent is needed could lead to problems. For example, if not all respondents consent, the sample size of the linked data set decreases. Additionally, consent bias might occur in the case of systematic differences between consenters and non-consenters. Compared to the number of studies asking for consent to record linkage, relatively little is known about the mechanisms behind the consent question.

Papers in this session focus on experiences and consequences when asking respondents for consent to record linkage in a survey. Topics might include issues such as determinants of consent; ways to increase consent rates; interviewer effects on consent; consent bias; experimenting with consent questions; consequences of asking for consent; etc.

Proposals should be no more than 500 words in length and should also be sent to Korbmacher@mea.mpisoc.mpg.de.


Linking Survey and Administrative Records: Processes and selectivities of consent 2Ms Julie Korbmacher
Researchers are invited to submit presentation proposals at the session "Linking Survey and Administrative Records: Processes and selectivities of consent" at the European Survey Research Association conference, July, 15-19, 2013 in Ljubljana.

The number of studies linking survey and administrative records is still increasing in the social sciences. There are two ways how to link data, with different implications. In statistical or propensity score matching sample units from a survey are matched to "similar" (in a statistical sense) units in the administrative records. The other way is to link the two data sources directly which requires respondents' consent. The latter approach is usually thought to be more promising, but the fact the respondents' consent is needed could lead to problems. For example, if not all respondents consent, the sample size of the linked data set decreases. Additionally, consent bias might occur in the case of systematic differences between consenters and non-consenters. Compared to the number of studies asking for consent to record linkage, relatively little is known about the mechanisms behind the consent question.

Papers in this session focus on experiences and consequences when asking respondents for consent to record linkage in a survey. Topics might include issues such as determinants of consent; ways to increase consent rates; interviewer effects on consent; consent bias; experimenting with consent questions; consequences of asking for consent; etc.

Proposals should be no more than 500 words in length and should also be sent to Korbmacher@mea.mpisoc.mpg.de.


Privacy Preserving Record-Linkage TechniquesProfessor Rainer Schnell
Linking survey data to administrative data is gaining more importance every day, even more in Official Statistics. Most survey-researchers concentrate on the willingness of respondents, to give the permission to link their responses to databases. In many countries, such linkages are possible under severe legal constraints, even when no permission by respondents has been given. In such conditions, the identifying information of respondents must be protected by special technical means, for example fault tolerant encrypted identifiers. Such measures are also necessary, when respondent data must be linked to databases, but no Personal Identification Number is available or allowed. Since millions of records must be linked to the sample size of the survey (usually between 1000-30000 respondents), the correct linking of protected identifiers is of utmost importance for this kind of research. Examples for this kind of surveys are large scale medical projects, census based surveys and large scale panels, for example in France, Germany and Switzerland. We would like to discuss the different ongoing projects with colleagues from survey organizations across Europe.