Fitting Generalized Estimating Equation (GEE) Regression Models in Stata

Nicholas Horton

No 1.1, North American Stata Users' Group Meetings 2001 from Stata Users Group

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.

Date: 2001-01-15
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://fmwww.bc.edu/RePEc/nasug2001/statagee.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:asug01:1.1

Access Statistics for this paper

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