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Abstract Details
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Activity Number:
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34
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Type:
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Contributed
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Date/Time:
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Sunday, July 31, 2011 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #301856 |
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Title:
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Optimal Longitudinal Cohort Designs and Parameter Estimation
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Author(s):
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Lu Gan*+ and Subir Ghosh
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Companies:
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University of California at Riverside and University of California at Riverside
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Address:
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Department of Statistics, Riverside, CA, 92521,
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Keywords:
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Cohort Design ;
Design Optimality ;
Mixed Effects ;
Model REML ;
Variance Estimation
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Abstract:
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For a longitudinal study in two cohorts with n subjects each, the observations are taken at three different time points denoted by (-1, x, 1) where -1 < x < 1. Our class of longitudinal cohort designs is{(-1, x1, 1) (-1, x2, 1); -1 < x1 = x2< 1}. For a linear mixed effects model, we obtain designs for estimating the fixed effects parameters under the standard D-, A-, and E- optimality criteria. We present the Restricted Maximum Likelihood (REML) estimates of variance components under certain model assumptions.
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