Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/37088
標題: A robust approach to t linear mixed models applied to multiple sclerosis data
作者: Lin, T.I.
林宗儀
Lee, J.C.
關鍵字: fisher scoring
longitudinal data
prediction
random effects
t-REML
longitudinal data
covariance-structures
variance-components
regression
inference
time
期刊/報告no:: Statistics in Medicine, Volume 25, Issue 8, Page(s) 1397-1412.
摘要: We discuss a robust extension of linear mixed models based on the multivariate t distribution. Since longitudinal data are successively collected over time and typically tend to be autocorrelated, we employ a parsimonious first-order autoregressive dependence structure for the within-subject errors. A score test statistic for testing the existence of autocorrelation among the within-subject errors is derived. Moreover, we develop an explicit scoring procedure for the maximum likelihood estimation with standard errors as a by-product. The technique for predicting future responses of a subject given past measurements is also investigated. Results are illustrated with real data from a multiple sclerosis clinical trial. Copyright (c) 2005 John Wiley & Sons, Ltd.
URI: http://hdl.handle.net/11455/37088
ISSN: 0277-6715
文章連結: http://dx.doi.org/10.1002/sim.2384
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