Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/37092
標題: Estimation and prediction in linear mixed models with skew-normal random effects for longitudinal data
作者: Lin, T.I.
林宗儀
Lee, J.C.
關鍵字: ECME algorithm
maximum-likelihood estimation
prediction
random
effects
SNLMM
multivariate-t-distribution
maximum-likelihood
bayesian-analysis
distributions
algorithm
extension
families
ecm
em
期刊/報告no:: Statistics in Medicine, Volume 27, Issue 9, Page(s) 1490-1507.
摘要: This paper extends the classical linear mixed model by considering a multivariate skew-normal assumption for the distribution of random effects. We present an efficient hybrid ECME-NR algorithm for the computation of maximum-likelihood estimates of parameters. A score test statistic for testing the existence of skewness preference among random effects is developed. The technique for the prediction of future responses under this model is also investigated. The methodology is illustrated through an application to Framingham cholesterol data and a simulation study. Copyright (C) 2007 John Wiley & Sons, Ltd.
URI: http://hdl.handle.net/11455/37092
ISSN: 0277-6715
文章連結: http://dx.doi.org/10.1002/sim.3026
Appears in Collections:統計學研究所

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