title: Balanced covariates with response adaptive randomization.
abstract: Response adaptive randomization (RAR) methods for clinical trials are susceptible to imbalance in the distribution of influential covariates across treatment arms. This can make the interpretation of trial results difficult, because observed differences between treatment groups may be a function of the covariates and not necessarily because of the treatments themselves. We propose a method for balancing the distribution of covariate strata across treatment arms within RAR. The method uses odds ratios to modify global RAR probabilities to obtain stratum-specific modified RAR probabilities. We provide illustrative examples and a simple simulation study to demonstrate the effectiveness of the strategy for maintaining covariate balance. The proposed method is straightforward to implement and applicable to any type of RAR method or outcome.
authors.affiliation: Berry Consultants, Austin, TX, 78746, USA.|Adjunct Faculty, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA.
authors.forename: Benjamin R
authors.identifier: 0000-0001-6058-7171
authors.initials: BR
authors.lastname: Saville
authors.affiliation: Berry Consultants, Austin, TX, 78746, USA.|Adjunct Faculty, Department of Biostatistics, University of Kansas Medical Center, Kansas City, KS, 66160, USA.
authors.forename: Scott M
authors.initials: SM
authors.lastname: Berry
mesh_terms: D002985:Clinical Protocols; D003198:Computer Simulation; D011336:Probability; D011897:Random Allocation; D016032:Randomized Controlled Trials as Topic
keywords: Bayesian RAR, clinical trial, covariate balance, imbalance, response adaptive randomization, stratification