ESTIMATION IN MULTIVARIATE t LINEAR MIXED MODELS FOR MULTIPLE LONGITUDINAL DATA

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题名:	ESTIMATION IN MULTIVARIATE t LINEAR MIXED MODELS FOR MULTIPLE LONGITUDINAL DATA
作者:	Wang,WL;Fan,TH
贡献者:	統計研究所
关键词:	MAXIMUM-LIKELIHOOD INFERENCE;BAYESIAN-ANALYSIS;DISTRIBUTIONS;ALGORITHM;ECM;ERRORS;MCMC;EM
日期:	2011
上传时间:	2012-03-27 19:07:57 (UTC+8)
出版者:	國立中央大學
摘要:	The multivariate linear mixed model (MLMM) is a frequently used tool for a joint analysis of more than one series of longitudinal data. Motivated by a concern of sensitivity to potential outliers or data with longer-than-normal tails and possible serial correlation, we develop a robust generalization of the MLMM that is constructed by using the multivariate t distribution and a parsimonious AR(p) dependence structure for the within-subject errors. A score test for the inspection of autocorrelation among within-subject errors is derived. A hybrid ECME-scoring procedure is developed for computing the maximum likelihood estimates with standard errors as a by-product. The methodology is illustrated through an application to a set of AIDS data and several simulation studies.
關聯:	STATISTICA SINICA
显示于类别:	[統計研究所] 期刊論文

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