We consider response adaptive designs when the binary response may be misclassified and extend relevant results in the literature. We derive the optimal allocations under various objectives and examine the relationship between the power of statistical test and the variability of treatment allocation. Asymptotically best response adaptive randomization procedures and effects of misclassification on the optimal allocations are investigated. A real-life clinical trial is also discussed to illustrate our proposed approach.
Bibliographical noteFunding Information:
The authors thank two anonymous referees, the Associate Editor, and the Editor for their insightful comments, which resulted in a substantially improved version of this paper. Xuan Li would also like to thank Dr. Yanqing Yi, Memorial University of Newfoundland, for helpful discussions. Xikui Wang’s research is funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada.
Copyright 2013 Elsevier B.V., All rights reserved.
- Optimal allocation
- Response adaptive designs