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Panel Attrition

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  • Peter Lugtig

Abstract

Attrition is the process of dropout from a panel study. Earlier studies into the determinants of attrition study respondents still in the survey and those who attrited at any given wave of data collection. In many panel surveys, the process of attrition is more subtle than being either in or out of the study. Respondents often miss out on one or more waves, but might return after that. They start off responding infrequently, but more often later in the course of the study. Using current analytical models, it is difficult to incorporate such response patterns in analyses of attrition. This article shows how to study attrition in a latent class framework. This allows the separation of different groups of respondents, that each follow a different and distinct process of attrition. Classifying attriting respondents enables us to formally test substantive theories of attrition and its effects on data accuracy more effectively.

Suggested Citation

  • Peter Lugtig, 2014. "Panel Attrition," Sociological Methods & Research, , vol. 43(4), pages 699-723, November.
  • Handle: RePEc:sae:somere:v:43:y:2014:i:4:p:699-723
    DOI: 10.1177/0049124113520305
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    References listed on IDEAS

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    1. Cheti Nicoletti & Franco Peracchi & Vincenzo Atella, 2005. "Survey Response and Survey Characteristics: Micro-level Evidence from the European Commission Household Panel," CEIS Research Paper 64, Tor Vergata University, CEIS.
    2. Cheti Nicoletti & Franco Peracchi, 2005. "Survey response and survey characteristics: microlevel evidence from the European Community Household Panel," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(4), pages 763-781, November.
    3. John Fitzgerald & Peter Gottschalk & Robert Moffitt, 1998. "An Analysis of Sample Attrition in Panel Data: The Michigan Panel Study of Income Dynamics," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 251-299.
    4. Lee A. Lillard & Constantijn W. A. Panis, 1998. "Panel Attrition from the Panel Study of Income Dynamics: Household Income, Marital Status, and Mortality," Journal of Human Resources, University of Wisconsin Press, vol. 33(2), pages 437-457.
    5. Gilles Celeux & Gilda Soromenho, 1996. "An entropy criterion for assessing the number of clusters in a mixture model," Journal of Classification, Springer;The Classification Society, vol. 13(2), pages 195-212, September.
    6. Andrew M. Jones & Xander Koolman & Nigel Rice, 2006. "Health‐related non‐response in the British Household Panel Survey and European Community Household Panel: using inverse‐probability‐weighted estimators in non‐linear models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 543-569, July.
    7. Daniel H. Hill & Robert J. Willis, 2001. "Reducing Panel Attrition: A Search for Effective Policy Instruments," Journal of Human Resources, University of Wisconsin Press, vol. 36(3), pages 416-438.
    8. Noah Uhrig, S.C., 2008. "The nature and causes of attrition in the British Household Panel Study," ISER Working Paper Series 2008-05, Institute for Social and Economic Research.
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