Model Selection Criterion Based on the Multivariate Quasi-Likelihood for Generalized Estimating Equations

被引:9
作者
Imori, Shinpei [1 ]
机构
[1] Osaka Univ, Grad Sch Engn Sci, Toyonaka, Osaka 5608531, Japan
基金
日本学术振兴会;
关键词
generalized estimating equations; longitudinal data analysis; model selection; multivariate quasi-likelihood; OF-FIT TESTS; LINEAR-MODELS; LONGITUDINAL DATA; GEE;
D O I
10.1111/sjos.12160
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The generalized estimating equations (GEE) approach has attracted considerable interest for the analysis of correlated response data. This paper considers the model selection criterion based on the multivariate quasi-likelihood (MQL) in the GEE framework. The GEE approach is closely related to the MQL. We derive a necessary and sufficient condition for the uniqueness of the risk function based on the MQL by using properties of differential geometry. Furthermore, we establish a formal derivation of model selection criterion as an asymptotically unbiased estimator of the prediction risk under this condition, and we explicitly take into account the effect of estimating the correlation matrix used in the GEE procedure.
引用
收藏
页码:1214 / 1224
页数:11
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