Bayesian optimal response-adaptive design for binary responses using stopping rule. (March 2018)

• Record Type: Journal Article
• Authors: Komaki, Fumiyasu; Biswas, Atanu
• Other Names: Nakas Christos T guest-editor.; Reiser Benjamin guest-editor.
• Is Part Of: Statistical methods in medical research. Volume 27:Number 3(2018)
• Page Start: 891
• Page End: 904
• Publication Date: 2018-03
• Subjects: Bayesian design -- ethics -- proportion of allocation -- non-informative prior -- sample size -- sequential design; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280216647210
• Languages: English
• ISSNs: 0962-2802

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.