Modelling of covariance structures in generalised estimating equations for longitudinal data

被引:96
作者
Ye, Huajun [1 ]
Pan, Jianxin [1 ]
机构
[1] Univ Manchester, Sch Math, Manchester M60 1QD, Lancs, England
基金
英国工程与自然科学研究理事会;
关键词
Cholesky decomposition; efficiency; generalised estimating equation; longitudinal data; misspecification of covariance structure; modelling of mean and covariance structures;
D O I
10.1093/biomet/93.4.927
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
When used for modelling longitudinal data generalised estimating equations specify a working structure for the within-subject covariance matrices, aiming to produce efficient parameter estimators. However, misspecification of the working covariance structure may lead to a large loss of efficiency of the estimators of the mean parameters. In this paper we propose an approach for joint modelling of the mean and covariance structures of longitudinal data within the framework of generalised estimating equations. The resulting estimators for the mean and covariance parameters are shown to be consistent and asymptotically Normally distributed. Real data analysis and simulation studies show that the proposed approach yields e?cient estimators for both the mean and covariance parameters.
引用
收藏
页码:927 / 941
页数:15
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