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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