The Annals of Statistics

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

Feifang Hu and Li-Xin Zhang

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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.

Article information

Ann. Statist., Volume 32, Number 1 (2004), 268-301.

First available in Project Euclid: 12 March 2004

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Zentralblatt MATH identifier

Primary: 60F15: Strong theorems 62G10: Hypothesis testing

Adaptive randomized design asymptotic normality randomized play-the-winner rule urn model


Hu, Feifang; Zhang, Li-Xin. Asymptotic properties of doubly adaptive biased coin designs for multitreatment clinical trials. Ann. Statist. 32 (2004), no. 1, 268--301. doi:10.1214/aos/1079120137.

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