A note on conditional AIC for linear mixed-effects models

doi:10.1093/biomet/asn023

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	A note on conditional AIC for linear mixed-effects models
	Liang, Hua 1; Wu, Hulin 1; Zou, Guohua 2
	2008-09-01
发表期刊	BIOMETRIKA
ISSN	0006-3444
卷号	95 期号:3 页码:773-778
摘要	The conventional model selection criterion, the Akaike information criterion, AIC, has been applied to choose candidate models in mixed-effects models by the consideration of marginal likelihood. Vaida & Blanchard (2005) demonstrated that such a marginal AIC and its small sample correction are inappropriate when the research focus is on clusters. Correspondingly, these authors suggested the use of conditional AIC. Their conditional AIC is derived under the assumption that the variance-covariance matrix or scaled variance-covariance matrix of random effects is known. This note provides a general conditional AIC but without these strong assumptions. Simulation studies show that the proposed method is promising.
关键词	Akaike information criterion conditional likelihood longitudinal data marginal likelihood mixed-effects model model selection
DOI	10.1093/biomet/asn023
语种	英语
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology ; Mathematics
WOS类目	Biology ; Mathematical & Computational Biology ; Statistics & Probability
WOS记录号	WOS:000258861000018
出版者	OXFORD UNIV PRESS
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/6191
专题	中国科学院数学与系统科学研究院
通讯作者	Liang, Hua
作者单位	1.Univ Rochester, Med Ctr, Dept Biostat & Computat Biol, Rochester, NY 14642 USA 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Liang, Hua,Wu, Hulin,Zou, Guohua. A note on conditional AIC for linear mixed-effects models[J]. BIOMETRIKA,2008,95(3):773-778.
APA	Liang, Hua,Wu, Hulin,&Zou, Guohua.(2008).A note on conditional AIC for linear mixed-effects models.BIOMETRIKA,95(3),773-778.
MLA	Liang, Hua,et al."A note on conditional AIC for linear mixed-effects models".BIOMETRIKA 95.3(2008):773-778.