Working correlation structure selection in generalized estimating equations
Journal article
Fu, Liya, Hao, Yangyang and Wang, You-Gan. (2018). Working correlation structure selection in generalized estimating equations. Computational Statistics. 33(2), pp. 983-996. https://doi.org/10.1007/s00180-018-0800-4
Authors | Fu, Liya, Hao, Yangyang and Wang, You-Gan |
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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 |
Year | 2018 |
Journal | Computational Statistics |
Journal citation | 33 (2), pp. 983-996 |
Publisher | Springer |
ISSN | 0943-4062 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s00180-018-0800-4 |
Scopus EID | 2-s2.0-85042624002 |
Page range | 983-996 |
Funder | Australian Research Council (ARC) |
National Natural Science Foundation of China (NSFC) | |
Ministry of Education of China | |
Fundamental Research Funds for the Central Universities | |
Publisher's version | License All rights reserved File Access Level Controlled |
Output status | Published |
Publication dates | |
Online | 28 Feb 2018 |
Publication process dates | |
Accepted | 15 Feb 2018 |
Deposited | 12 Dec 2022 |
ARC Funded Research | This output has been funded, wholly or partially, under the Australian Research Council Act 2001 |
Grant ID | DP130100766 |
DP160104292 | |
11201365 | |
11301408 | |
2012020112005 | |
xjj2017180 |
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