Professor Min Yang : Optimal crossover designs

Posted by , part of the Statistics and Data Science Seminar.

At

March 29, 2006, 10 a.m.

In

SEO 512

Abstract

Crossover designs, where experimental subjects are used in two or more (p) periods for the purpose of evaluating and studying two or more (t) treatments, originated from agricultural studies and have proven widely effective in a variety of fields, especially in phase I and phase II pharmaceutical clinical trials. The rigorous study of these designs and their optimality and efficiency has a history of more than 3 decades. In this talk, we will review and study the optimality, efficiency, and robustness of crossover designs under the following two different situations (i) all treatment comparisons are equally important and (ii) for comparing several test treatments to a control treatment. Two algorithms, both guided by these efficiencies and results from optimal design theory, are proposed for obtaining efficient designs under the various models.

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