Repository logo
 

Familywise error rate control for block response-adaptive randomization.

Published version
Peer-reviewed

Repository DOI


Change log

Authors

Abstract

Response-adaptive randomization allows the probabilities of allocating patients to treatments in a clinical trial to change based on the previously observed response data, in order to achieve different experimental goals. One concern over the use of such designs in practice, particularly from a regulatory viewpoint, is controlling the type I error rate. To address this, Robertson and Wason (Biometrics, 2019) proposed methodology that guarantees familywise error rate control for a large class of response-adaptive designs by re-weighting the usual z-test statistic. In this article, we propose an improvement of their method that is conceptually simpler, in the context where patients are allocated to the experimental treatment arms in a trial in blocks (i.e. groups) using response-adaptive randomization. We show the modified method guarantees that there will never be negative weights for the contribution of each block of data to the adjusted test statistics, and can also provide a substantial power advantage in practice.

Description

Peer reviewed: True


Funder: Biometrika Trust

Keywords

Conditional invariance principle, multiple testing, power, type I error rate, Humans, Random Allocation, Research Design, Probability

Journal Title

Stat Methods Med Res

Conference Name

Journal ISSN

0962-2802
1477-0334

Volume Title

32

Publisher

SAGE Publications
Sponsorship
Medical Research Council (MC_UU_00002/14)
National Institute for Health and Care Research (IS-BRC-1215-20014)