Fitting Generalized Estimating Equation (GEE) Regression Models in Stata

Researchers are often interested in analyzing data which arise from a longitudinal or clustered design. While there are a variety of standard likelihood-based approaches to analysis when the outcome variables are approximately multivariate normal, models for discrete-type outcomes generally require a different approach. Liang and Zeger formalized an approach to this problem using Generalized Estimating Equations (GEEs) to extend Generalized Linear Models (GLMs) to a regression setting with correlated observations within subjects. In this talk, I will briefly review the GEE methodology, introduce some examples, and provide a tutorial on how to fit models using "xtgee" in Stata.