  Response adaptive randomization (RAR) is appealing from methodological,
ethical, and pragmatic perspectives in the sense that subjects are more likely
to be randomized to better performing treatment groups based on accumulating
data. However, applications of RAR in confirmatory drug clinical trials with
multiple active arms are limited largely due to its complexity, and lack of
control of randomization ratios to different treatment groups. To address the
aforementioned issues, we propose a Response Adaptive Block Randomization
(RABR) design allowing arbitrarily pre-specified randomization ratios for the
control and high-performing groups to meet clinical trial objectives. We show
the validity of the conventional unweighted test in RABR with a controlled type
I error rate based on the weighted combination test for sample size adaptive
design invoking no large sample approximation. The advantages of the proposed
RABR in terms of robustly reaching target final sample size to meet regulatory
requirements and increasing statistical power as compared with the popular
Doubly Adaptive Biased Coin Design (DBCD) are demonstrated by statistical
simulations and a practical clinical trial design example.
