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National Chung Hsing University Institutional Repository - NCHUIR > 理學院 > 統計學研究所 > 依資料類型分類 > 期刊論文 >  Bayesian analysis of hierarchical linear mixed modeling using the multivariate t distribution

Please use this identifier to cite or link to this item: http://nchuir.lib.nchu.edu.tw/handle/309270000/133591

標題: Bayesian analysis of hierarchical linear mixed modeling using the multivariate t distribution
作者: Lin, T.I.;Lee, J.C.
林宗儀
關鍵字: autoregressive process;Bayesian prediction;Markov chain Monte Carlo;missing values;random effects;t linear mixed models;longitudinal data;covariance-structures;growth-curves;inference;time
日期: 2007
Issue Date: 2012-12-14 10:05:52 (UTC+8)
關連: Journal of Statistical Planning and Inference, Volume 137, Issue 2, Page(s) 484-495.
摘要: This article presents a fully Bayesian approach to modeling incomplete longitudinal data using the t linear mixed model with AR(p) dependence. Markov chain Monte Carlo (MCMC) techniques are implemented for computing posterior distributions of parameters. To facilitate the computation, two types of auxiliary indicator matrices are incorporated into the model. Meanwhile, the constraints on the parameter space arising from the stationarity conditions for the autoregressive parameters are handled by a reparametrization scheme. Bayesian predictive inferences for the future vector are also investigated. An application is illustrated through a real example from a multiple sclerosis clinical trial. (c) 2006 Elsevier B.V. All rights reserved.
Relation: Journal of Statistical Planning and Inference
Appears in Collections:[依資料類型分類] 期刊論文
[依教師分類] 林宗儀
[依教師分類] 林宗儀

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