Asymptotic properties of doubly adaptive biased coin designs for multitreatment clinical trials

• 成果类型: Article
• 署名作者: Hu, FF; Zhang, LX
• 署名单位: University of Virginia; Zhejiang University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 2004
• 页码: 268-301
• 关键词: CENTRAL LIMIT-THEOREMS; play-winner rule; medical trials; urn models; probability; tests

摘要

A general doubly adaptive biased coin design is proposed for the allocation of subjects to K treatments in a clinical trial. This design follows the same spirit as Efron's biased coin design and applies to the cases where the desired allocation proportions are unknown, but estimated sequentially. Strong consistency, a law of the iterated logarithm and asymptotic normality of this design are obtained under some widely satisfied conditions. For two treatments, a new family of designs is proposed and shown to be less variable than both the randomized play-the-winner rule and the adaptive randomized design. Also the proposed design tends toward a randomization scheme (with a fixed target proportion) as the size of the experiment increases.