期刊
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
卷 102, 期 477, 页码 224-234出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/016214506000000906
关键词
clinical trials; doubly adaptive biased coin design; Neyman allocation; power; response-adaptive randomization
For sequential experiments with K treatments, we establish two formal optimization criteria to find optimal allocation strategies. Both criteria involve the sample sizes on each treatment and a concave noncentrality parameter from a multivariate test. We show that these two criteria are equivalent. We apply this result to specific questions: (1) How do we maximize power of a multivariate test of homogeneity with binary response?, and (2) for fixed power, how do we minimize expected treatment failures? Because the solutions depend on unknown parameters, we describe a response-adaptive randomization procedure that targets the optimal allocation and provides increases in power along the lines of 2-4% over complete randomization for equal allocation. The increase in power contradicts the conclusions of other authors who have explored other randomization procedures for K = 2 and have found that the variability induced by randomization negates any benefit of targeting an optimal allocation.
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