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

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.