Working correlation structure selection in generalized estimating equations

Liya Fu (), Yangyang Hao () and You-Gan Wang ()
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Liya Fu: Xi’an Jiaotong University
Yangyang Hao: Shanghai Maritime University
You-Gan Wang: Queensland University of Technology

Computational Statistics, 2018, vol. 33, issue 2, No 18, 983-996

Abstract: Abstract Selecting an appropriate correlation structure in analyzing longitudinal data can greatly improve the efficiency of parameter estimation, which leads to more reliable statistical inference. A number of such criteria have been proposed in the literature from different perspectives. However, little is known about the relative performance of these criteria. We review and evaluate these criteria by carrying out extensive simulation studies. Surprisingly, we find that the AIC and the BIC based on either the Gaussian working likelihood or the empirical likelihood outperform the others.

Keywords: Correlation information criterion; Empirical likelihood; Longitudinal data; Model selection (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s00180-018-0800-4

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