The Annals of Statistics

$K$-Treatment Comparisons with Restricted Randomization Rules in Clinical Trials

L. J. Wei, R. T. Smythe, and R. L. Smith

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In the course of conducting a clinical trial to compare $K (\geq 2)$ treatments, it is often desirable to balance the trial with respect to the assignments of patients to treatments. On the other hand, some form of randomization of treatment assignments is essential for reducing experimental bias. In this article, the large-sample approximation to the null distribution of $K$-sample randomization tests generated from a broad class of restricted randomization rules is derived. The implication of this result for conditional inference is also discussed.

Article information

Ann. Statist. Volume 14, Number 1 (1986), 265-274.

First available in Project Euclid: 12 April 2007

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Digital Object Identifier

Mathematical Reviews number (MathSciNet)

Zentralblatt MATH identifier

Primary: 62L05: Sequential design
Secondary: 60K30: Applications (congestion, allocation, storage, traffic, etc.) [See also 90Bxx]

Biased coin design conditional inference martingale central limit theorem randomization model urn design


Wei, L. J.; Smythe, R. T.; Smith, R. L. $K$-Treatment Comparisons with Restricted Randomization Rules in Clinical Trials. The Annals of Statistics 14 (1986), no. 1, 265--274. doi:10.1214/aos/1176349854.

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