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Bayesian optimal response-adaptive design for binary responses using stopping rule.

Authors
  • Komaki, Fumiyasu1, 2
  • Biswas, Atanu3
  • 1 1 Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan. , (Japan)
  • 2 2 RIKEN Brain Science Institute, Wakō, Japan. , (Japan)
  • 3 3 Applied Statistics Unit, Indian Statistical Institute, Kolkata, India. , (India)
Type
Published Article
Journal
Statistical Methods in Medical Research
Publisher
SAGE Publications
Publication Date
Mar 01, 2018
Volume
27
Issue
3
Pages
891–904
Identifiers
DOI: 10.1177/0962280216647210
PMID: 27142983
Source
Medline
Keywords
License
Unknown

Abstract

Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.

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