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Looking Beyond Demographics: Panel Attrition in the ANES and GSS

Published online by Cambridge University Press:  04 January 2017

Laura Lazarus Frankel  and
D. Sunshine Hillygus
Laura Lazarus Frankel
Affiliation:
Department of Political Science, Duke University, 140 Science Drive, Box 90204, Durham, NC 27708
D. Sunshine Hillygus*
Affiliation:
Department of Political Science, Duke University, 140 Science Drive, Box 90204, Durham, NC 27708
*
e-mail: [email protected] (corresponding author)
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Abstract

Longitudinal or panel surveys offer unique benefits for social science research, but they typically suffer from attrition, which reduces sample size and can result in biased inferences. Previous research tends to focus on the demographic predictors of attrition, conceptualizing attrition propensity as a stable, individual-level characteristic—some individuals (e.g., young, poor, residentially mobile) are more likely to drop out of a study than others. We argue that panel attrition reflects both the characteristics of the individual respondent as well as her survey experience, a factor shaped by the design and implementation features of the study. In this article, we examine and compare the predictors of panel attrition in the 2008–2009 American National Election Study, an online panel, and the 2006–2010 General Social Survey, a face-to-face panel. In both cases, survey experience variables are predictive of panel attrition above and beyond the standard demographic predictors, but the particular measures of relevance differ across the two surveys. The findings inform statistical corrections for panel attrition bias and provide study design insights for future panel data collections.

Type
Symposium on Advances in Survey Methodology
Information
Political Analysis , Volume 22 , Issue 3 , Summer 2014 , pp. 336 - 353
Copyright
Copyright © The Author 2014. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors' note: Laura Lazarus Frankel is a Ph.D. candidate in political science at Duke University. D. Sunshine Hillygus is an Associate Professor of Political Science at Duke University. An earlier version of this paper was presented at the Annual Meeting of the American Association of Public Opinion Research. Replication data are available on the Political Analysis Dataverse.

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