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Cited by 2,493

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Akaike's Information Criterion in Generalized Estimating Equations

Pan, Wei·2001·Biometrics

Abstract

Summary. Correlated response data are common in biomedical studies. Regression analysis based on the generalized estimating equations (GEE) is an increasingly important method for such data. However, there seem to be few model‐selection criteria available in GEE. The well‐known Akaike Information Criterion (AIC) cannot be directly applied since AIC is based on maximum likelihood estimation while GEE is nonlikelihood based. We propose a modification to AIC, where the likelihood is replaced by the quasi‐likelihood and a proper adjustment is made for the penalty term. Its performance is investigated through simulation studies. For illustration, the method is applied to a real data set.

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Metadata

Authors
Pan, W.
Venue
Biometrics
Published
2001-03
Volume
57
Issue
1
Pages
120-125
ISSN
  • 0006-341X (ISSN-L)
  • 1541-0420
OpenAlex
W2110776215
Cited by
2,493
References
2
FWCI
10.24
Type
journal article
Language
en
Open access
closed

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