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An Introduction to Generalized Estimating Equations and an Application to Assess Selectivity Effects in a Longitudinal Study on Very Old Individuals

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  • Paolo Ghisletta
  • Dario Spini

Abstract

Correlated data are very common in the social sciences. Most common applications include longitudinal and hierarchically organized (or clustered) data. Generalized estimating equations (GEE) are a convenient and general approach to the analysis of several kinds of correlated data. The main advantage of GEE resides in the unbiased estimation of population-averaged regression coefficients despite possible misspecification of the correlation structure. This article aims to provide a concise, nonstatistical introduction to GEE. To illustrate the method, an analysis of selectivity effects in the Swiss Interdisciplinary Longitudinal Study on the Oldest Old is presented.

Suggested Citation

  • Paolo Ghisletta & Dario Spini, 2004. "An Introduction to Generalized Estimating Equations and an Application to Assess Selectivity Effects in a Longitudinal Study on Very Old Individuals," Journal of Educational and Behavioral Statistics, , vol. 29(4), pages 421-437, December.
    • Handle: RePEc:sae:jedbes:v:29:y:2004:i:4:p:421-437
    DOI: 10.3102/10769986029004421
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    1. Julie A. Teichroeb & Eva C. Wikberg & Iulia Bădescu & Lisa J. Macdonald & Pascale Sicotte, 2012. "Infanticide risk and male quality influence optimal group composition for Colobus vellerosus," Behavioral Ecology, International Society for Behavioral Ecology, vol. 23(6), pages 1348-1359.
    2. Kobelsky, Kevin W. & Robinson, Michael A., 2010. "The impact of outsourcing on information technology spending," International Journal of Accounting Information Systems, Elsevier, vol. 11(2), pages 105-119.
    3. Leitner, Jordan B. & Hehman, Eric & Ayduk, Ozlem & Mendoza-Denton, Rodolfo, 2016. "Racial bias is associated with ingroup death rate for Blacks and Whites: Insights from Project Implicit," Social Science & Medicine, Elsevier, vol. 170(C), pages 220-227.
    4. Gary N. Marks, 2018. "Do the labour market returns to university degrees differ between high and low achieving youth? Evidence from Australia," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 52(1), pages 1-14, December.
    5. Hansen, Nele & Kupfer, Ann-Kristin & Hennig-Thurau, Thorsten, 2018. "Brand crises in the digital age: The short- and long-term effects of social media firestorms on consumers and brands," International Journal of Research in Marketing, Elsevier, vol. 35(4), pages 557-574.

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