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Methods Inf Med 2010; 49(05): 421-425
DOI: 10.3414/ME10-01-0026
Original Articles
Schattauer GmbH

Generalized Estimating Equations

Notes on the Choice of the Working Correlation Matrix
A. Ziegler
1   Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Lübeck, Germany
,
M. Vens
1   Institut für Medizinische Biometrie und Statistik, Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein, Lübeck, Germany
› Author Affiliations
Further Information

Publication History

received: 29 March 2010

accepted: 12 May 2010

Publication Date:
17 January 2018 (online)

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Summary

Background: Generalized estimating equations (GEE) are an extension of generalized linear models (GLM) in that they allow adjusting for correlations between observations. A major strength of GEE is that they do not require the correct specification of the multivariate distribution but only of the mean structure.

Objectives: Several concerns have been raised about the validity of GEE when applied to dichotomous dependent variables. In this contribution, we summarize the theoretical findings concerning efficiency and validity of GEE.

Methods: We introduce the GEE in a formal way, summarize general findings on the choice of the working correlation matrix, and show the existence of a dilemma for the optimal choice of the working correlation matrix for dichotomous dependent variables.

Results: Biological and statistical arguments for choosing a specific working correlation matrix are given. Three approaches are described for overcoming the range restriction of the correlation coefficient.

Conclusions: The three approaches described in this article for overcoming the range restrictions for dichotomous dependent variables in GEE models provide a simple and practical way for use in applications.

Keywords

Correlation matrix - generalized estimating equations - independence estimating equations - restriction of parameter space
 

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