Abstract #301178


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JSM 2002 Abstract #301178
Activity Number: 110
Type: Contributed
Date/Time: Monday, August 12, 2002 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section*
Abstract - #301178
Title: Asymptotic Optimal Sample Sizes for Discovering Promising Treatment in Phase II Group Sequential Clinical Trials.
Author(s): Yi Cheng*+ and Rosner Gary
Affiliation(s): Indiana University South Bend and U. T. M. D. Anderson Cancer Center
Address: 1700 Mishawaka Avenue, South Bend, Indiana, 46634, USA
Keywords: Phase II Clinical Trial ; Group Sequential Design ; Bayesian Analysis ; Optimal Sample Size ; Asymptotic Optimality
Abstract:

We propose an asymptotic optimal procedure in deciding the sample size for series of Phase II clinical screen trials for discovering a new promising treatment among a sequence of treatments. The trials are designed in r stages with r=1, 2, or 3. The criterion of the optimality is to minimize the total number of observations until one promising treatment is identified, while the probabilities of false positive and false negative are controlled under the given values. The asymptotic optimal sample sizes are given explicitly based on the theoretical results. The computation of the asymptotic optimal sample sizes is simple and straightforward, which is a great advantage in practice. The numerical comparison shows that the asymptotic optimal sample size and true optimal sample size are quite close. The Baysian formulation is used in the procedure, and the concerns in choosing prior distributions are discussed.


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