Empirical likelihood for generalized linear models with longitudinal data

Daoji Li and Jianxin Pan

Journal of Multivariate Analysis, 2013, vol. 114, issue C, 63-73

Abstract: 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.

Keywords: Empirical likelihood; Generalized estimating equations; Longitudinal data; Quadratic inference functions; Quasi-likelihood; Hypothesis testing (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:114:y:2013:i:c:p:63-73

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DOI: 10.1016/j.jmva.2012.07.014

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