Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/37047
標題: Robust linear mixed models using the skew t distribution with application to schizophrenia data
作者: Ho, H.J.
林宗儀
Lin, T.I.
關鍵字: AECM algorithm
Intermittent missing values
Outliers
Random effects
Skew t linear mixed model
longitudinal data
missing data
information matrix
bayesian-analysis
em algorithm
ecm
inference
mcmc
期刊/報告no:: Biometrical Journal, Volume 52, Issue 4, Page(s) 449-469.
摘要: We consider an extension of linear mixed models by assuming a multivariate skew t distribution for the random effects and a multivariate t distribution for the error terms. The proposed model provides flexibility in capturing the effects of skewness and heavy tails simultaneously among continuous longitudinal data. We present an efficient alternating expectation-conditional maximization (AECM) algorithm for the computation of maximum likelihood estimates of parameters on the basis of two convenient hierarchical formulations. The techniques for the prediction of random effects and intermittent missing values under this model are also investigated. Our methodologies are illustrated through an application to schizophrenia data.
URI: http://hdl.handle.net/11455/37047
ISSN: 0323-3847
文章連結: http://dx.doi.org/10.1002/bimj.200900184
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