Abstract #300080

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JSM 2003 Abstract #300080
Activity Number: 417
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Teaching of Statistics in the Health Sciences
Abstract - #300080
Title: D-Optimal and Maximin Designs for GLMM Models
Author(s): Frans E.S. Tan*+ and Martijn P. F. Berger
Companies: University of Maastricht and University of Maastricht
Address: PO Box 616, Maastricht, 6200 MD, Netherlands
Keywords: D-optimal ; maximin ; relative efficiency ; GLLM ; covariates ; sequential
Abstract:

When planning an experimental design, it is often advocated to randomly allocate an equal number of subjects to each of the groups of the treatment factor. In general, the primary virtue of this random allocation is to balance the treatment groups with respect to several covariates. From an optimal design perspective, it will be argued that the equal assignment strategy is not always optimal. General guidelines will be presented that characterize the optimal distribution of the treatment factor. Under certain conditions the minimum relative efficiency of the equal assignment strategy for all possible distributions of covariates is maximized. We will review our main findings on optimal allocation problems for generalized linear mixed models and discuss the optimal allocation problem when several important covariates are present.

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