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Abstract Details

Activity Number: 407
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
Sponsor: IMS
Abstract - #305109
Title: Simultaneous Testing of Multiple Hypotheses in Sequential Experiments
Author(s): Shyamal Krishna De*+
Companies: The University of Texas at Dallas
Address: Department of Mathematical Sciences, Richardson, TX, 75080-3021, United States
Keywords: Asymptotic optimality ; Familywise error rate ; Multiple comparisons ; Sequential probability ratio test ; Stopping rule

The problem of multiple hypotheses testing often arises in sequential experiments such as sequential clinical trials with multiple endpoints, acceptance sampling with different criteria of acceptance, multichannel change-point detection, etc. In such experiments, it is necessary to obtain a statistical decision for each individual hypothesis instead of combining them and giving one answer to the resulting composite hypothesis.

Combining classical ideas of sequential testing with non-sequential stepwise methods for multiple comparisons, sequential procedures are developed for tests of multiple hypotheses. Proposed methods control both familywise Type I and Type II error rates in the strong sense. Further, we attempt to minimize the expected sample size (expected cost) of the experiment under these constraints. Asymptotic optimality is achieved under the Pitman alternative. Extensive simulation study confirms that the new methods yield expected sample size approximately 50% lower than the corresponding expected sample sizes of earlier approaches.

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