Abstract
Generalized estimating equations (GEE) incorporate a working correlation structure that is important because the more accurately this structure reflects the true structure, the more efficiently regression parameters may be estimated. Numerous criteria have therefore been proposed to select a working structure, although no criterion will always work better than all other criteria. In practice, it will be unknown which criterion will work best. Therefore, in this manuscript we propose how to utilize information from multiple criteria. We demonstrate the benefits of our proposed approach via a simulation study in a variety of settings and then in an application example.
Original language | English |
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Pages (from-to) | 305-316 |
Number of pages | 12 |
Journal | Communications in Statistics Part B: Simulation and Computation |
Volume | 49 |
Issue number | 2 |
DOIs | |
State | Published - Feb 1 2020 |
Bibliographical note
Funding Information:We would like to thank Dr. Richard J. Kryscio, Dr. Frederick A. Schmitt, and Dr. Erin Abner for allowing us to use data from the PREADViSE trial, which was supported by a grant from the National Institute on Aging (R01 AG019241). We also thank two anonymous reviewers for their helpful comments that improved this manuscript.
Publisher Copyright:
© 2018, © 2018 Taylor & Francis Group, LLC.
Keywords
- Correlation structure
- covariance matrix
- efficiency
- empirical longitudinal data
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation