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Bias Correction in Generalized Linear Mixed Models with Multiple Components of Dispersion

 

作者: Xihong Lin,   NormanE. Breslow,  

 

期刊: Journal of the American Statistical Association  (Taylor Available online 1996)
卷期: Volume 91, issue 435  

页码: 1007-1016

 

ISSN:0162-1459

 

年代: 1996

 

DOI:10.1080/01621459.1996.10476971

 

出版商: Taylor & Francis Group

 

关键词: Asymptotic bias;Correlated data;Laplace approximation;Penalized quasi-likelihood;Random effects;Variance components

 

数据来源: Taylor

 

摘要:

General formulas are derived for the asymptotic bias in regression coefficients and variance components estimated by penalized quasi-likelihood (PQL) in generalized linear mixed models with canonical link function and multiple sets of independent random effects. Easily computed correction matrices result in variance component estimates that have satisfactory asymptotic behavior for small values of the variance components and significantly reduce bias for larger values. Both first-order and second-order correction procedures are developed for regression coefficients estimated by PQL. The methods are illustrated through an analysis of an experiment on salamander matings involving crossed male and female random effects, and their properties are evaluated in a simulation study.

 

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