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Subject specific and population average models for binary longitudinal data: a tutorial

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  • Szmaragd, Camille
  • Clarke, Paul
  • Steele, Fiona

Abstract

Using data from the British Household Panel Survey, we illustrate how longitudinal repeated measures of binary outcomes are analysed using population average and subject specific logistic regression models. We show how the autocorrelation found in longitudinal data is accounted for by both approaches, and why, in contrast to linear models for continuous outcomes, the parameters of population average and subject specific models for binary outcomes are different. To illustrate these points, we fit different models to our data set using both approaches, and compare and contrast the results obtained. Finally, we use our example to provide some guidance on how to choose between the two approaches.

Suggested Citation

  • Szmaragd, Camille & Clarke, Paul & Steele, Fiona, 2013. "Subject specific and population average models for binary longitudinal data: a tutorial," LSE Research Online Documents on Economics 52199, London School of Economics and Political Science, LSE Library.
  • Handle: RePEc:ehl:lserod:52199
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    1. James Cui, 2007. "QIC program and model selection in GEE analyses," Stata Journal, StataCorp LP, vol. 7(2), pages 209-220, June.
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    3. Verde, Stefano F. & Graf, Christoph & Jong, Thijs, 2019. "Installation entries and exits in the EU ETS: patterns and the delay effect of closure provisions," Energy Economics, Elsevier, vol. 78(C), pages 508-524.
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    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

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