Empirical likelihood for generalized linear models with longitudinal data

JOURNAL OF MULTIVARIATE ANALYSIS

卷:114

Article

Li, Daoji¹  Pan, Jianxin¹ 

[1] Univ Manchester, Sch Math, Manchester M13 9PL, Lancs, England

关键词: Empirical likelihood;    Generalized estimating equations;    Longitudinal data;    Quadratic inference functions;    Quasi-likelihood;    Hypothesis testing;   

DOI  :  10.1016/j.jmva.2012.07.014

来源: Elsevier

【 摘 要 】

In this paper, empirical likelihood-based inference for longitudinal data within the framework of generalized linear model is investigated. The proposed procedure takes into account the within-subject correlation without involving direct estimation of nuisance parameters in the correlation matrix and retains optimal even if the working correlation structure is misspecified. The proposed approach yields more efficient estimators than conventional generalized estimating equations and achieves the same asymptotic variance as quadratic inference function based methods. Furthermore, hypothesis testing procedures are developed to test whether or not the model assumption is met and whether or not regression coefficients are significant. The finite sample performance of the proposed methods is evaluated through simulation studies. Application to the Ohio Children Wheeze Status data is also discussed. (C) 2012 Elsevier Inc. All rights reserved.

【 授权许可】

Free