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Activity Number:
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113
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Type:
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Contributed
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Date/Time:
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Monday, August 3, 2009 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #303265 |
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Title:
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Test and Prediction in Multivariate Linear Mixed Models for Multiple Longitudinal Data
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Author(s):
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Wan-Lun Wang*+ and Tsai-Hung Fan
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Companies:
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National Central University and National Central University
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Address:
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Graduate Institute of Statistics, Jhongli City, Taoyuan County, 32049, Taiwan
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Keywords:
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ECM algorithm ; Empirical Bayes estimates ; Multiple outcomes ; Prediction ; Score test
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Abstract:
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For the analysis of longitudinal data with multiple characteristics, we are devoted to providing additional tools for multivariate linear mixed models (Shah A., Laird N., and Schoenfeld D., 1997. J. Amer. Stat. Assoc. 92, 775-779). We present a computationally flexible ECM procedure for obtaining the maximum likelihood estimates of parameters. A score test statistic for testing the existence of autocorrelation among within-subject errors of each characteristic is derived. The techniques for the estimation of random effects and the prediction of further responses given past repeated measures are also investigated. The methodology is illustrated through an application to a set of AIDS data.
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