Journal
STATISTICS IN MEDICINE
Volume 24, Issue 8, Pages 1245-1261Publisher
WILEY
DOI: 10.1002/sim.2023
Keywords
goodness of fit; GEE; clustered binary data; logistic regression; type I error; power
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Funding
- NIAID NIH HHS [5 U01 AI038855-08] Funding Source: Medline
- NINDS NIH HHS [2 U01 NS0322228-08A1] Funding Source: Medline
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Generalized estimating equations have become a popular regression method for analysing clustered binary data. Methods to assess the goodness of fit of the fitted models have recently been developed. However, evaluations and comparisons of these methods are limited. We discuss these methods and develop two additional statistics to evaluate goodness of fit. We evaluate the performance of each of the statistics with respect to type I error rates and power in a simulation study. Guidance is provided regarding appropriate use of the statistics under various scenarios. Copyright (c) 2004 John Wiley & Sons, Ltd.
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