JSM 2004 - Toronto

Abstract #300396

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Activity Number: 82
Type: Contributed
Date/Time: Monday, August 9, 2004 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #300396
Title: A Comparison of Goodness-of-fit Tests for the Logistic GEE Model C
Author(s): Scott R. Evans*+ and Lingling Li
Companies: Harvard University and Harvard University
Address: FXB-513/HSPH, Boston, MA, 02115,
Keywords: goodness-of-fit ; GEE ; clustered binary data ; logistic regression
Abstract:

The logistic Generalized Estimating Equations (GEE) model has become a widely used method of analysis for clustered binary data. The model is easily fit with readily available software. Output is easily interpreted and can be used to estimate probabilities and/or odds ratios. With this increase in application has been an increase in the development of methods to assess the adequacy of the fitted model. Assessment of the adequacy of the fitted GEE models has been a challenging area of research since no likelihood exists and residuals within cluster are correlated. Recently several goodness-of-fit statistics have been proposed; however, a comparison and evaluation of these methods is lacking. We review, compare, and evaluate these methods.

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