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Wednesday 15th July, 09:00 - 10:30 Room: O-201

Measurement errors in official statistical surveys
Convenor	Mr Anton Karlsson (Statistics Iceland )
Coordinator 1	Mr Øyvin Kleven (Statistics Norway)

Session Details

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.

Paper Details

1. Measurement error across modes in the Icelandic Labour Force Survey
Mr Anton Karlsson (Statistics Iceland)

One proposed solution for increasing response rates in surveys is to offer more than one mode in the data collection phase, possibly reducing non-response bias. The main problem of this approach is the possibility of measurement error differently affecting responses by the data collection method used. This presentation describes a split ballot test of collecting data for the Icelandic Labour Force Survey using a telephone interview, a web-questionnaire or mix of both modes. The main goal is to examine to which extent different modes can reduce possible non-response bias, without increasing the likelihood of measurement error in

2. Effects of dependent interviewing on respondents and interviewers
Ms Sophia Nebel (Federal Statistical Office of Germany )
Mr Daniel Zimmermann (Federal Statistical Office of Germany )

In the context of the reform of household statistics Germany plans to adopt an infra-annual rotation pattern for the Labour Force Survey, which will consequently reduce the distances between the interviews and increase the burden of households. Currently independent interviewing is used for conducting household surveys. Especially in panel studies respondents are confused by confronting them with recurring questions for several waves. Therefore the Federal Statistical Office of Germany is planning to implement dependent interviewing for the German microcensus.To test the feasibility of the technique the FSO carried out a pretest.The presentation focuses on results and challenges.

3. Adjusting measurement effects in mixed-mode inference: evaluation of an approach using re-interview data
Dr Thomas Klausch (Utrecht University / Statistics Netherlands)
Dr Barry Schouten (Utrecht University / Statistics Netherlands)

Measurement effects (MEs) are a problem in mixed-mode (MM) surveys threatening accuracy of MM estimates and may need to be adjusted after data collection. Our approach is based on the potential outcomes framework predicting outcomes of modes deemed more accurate, but not observed for all respondents. We suggest using re-interview data collected in addition to the MM data as auxiliary information, because available data from registers is typically weak. The viability of this approach is evaluated by simulation taking into account various factors, such as the size of the re-interview sample, costs, and efficiency of adjustments.

4. Detecting and correcting for measurement errors in election surveys by auxiliary information
Mr Oyvin Kleven (Statistics Norway)

For many surveys measurement errors is the most damaging source of error. Measurement errors may be difficult to detect unless they lead to illogical responses. One approach to detect measurement errors is to use auxiliary variables. Some textbooks mention the danger of a social desirability effect in reporting voting in election surveys (a higher chance of misreporting if one did not participate in the election and). In this presentation we illustrate this approach for bias exploration using the Norwegian Election Survey data. The claimed turnout in the survey can be checked individually against the true head-count from the electoral