Abstract:
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.
More papers in North American Stata Users' Group Meetings 2001 from Stata Users Group Contact information at EDIRC. Series data maintained by Christopher F Baum ().
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