The Annals of Statistics

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

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

Full-text: Open access

Abstract

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

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

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
http://projecteuclid.org/euclid.aos/1176349854

JSTOR
links.jstor.org

Digital Object Identifier
doi:10.1214/aos/1176349854

Mathematical Reviews number (MathSciNet)
MR829567

Zentralblatt MATH identifier
0587.62153

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

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

Citation

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. http://projecteuclid.org/euclid.aos/1176349854.


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