Statistical analysis of correlated data using generalized estimating equations: An orientation

James A. Hanley, Abdissa Negassa, Michael B. Edwardes, Janet E. Forrester

Research output: Contribution to journalArticlepeer-review

1405 Scopus citations


The method of generalized estimating equations (GEE) is often used to analyze longitudinal and other correlated response data, particularly if responses are binary. However, few descriptions of the method are accessible to epidemiologists. In this paper, the authors use small worked examples and one real data set, involving both binary and quantitative response data, to help end-users appreciate the essence of the method. The examples are simple enough to see the behind-the-scenes calculations and the essential role of weighted observations, and they allow nonstatisticians to imagine the calculations involved when the GEE method is applied to more complex multivariate data.

Original languageEnglish (US)
Pages (from-to)364-375
Number of pages12
JournalAmerican Journal of Epidemiology
Issue number4
StatePublished - Feb 15 2003


  • Correlation
  • Epidemiologic methods
  • Generalized estimating equation
  • Longitudinal studies
  • Odds ratio
  • Statistics

ASJC Scopus subject areas

  • Epidemiology


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