2008/08/01 by William F. Rosenberger, Oleksandr Sverdlov · 182 citations
Mathematics · Medicine · #Advanced Causal Inference Techniques #Balance (ability) #Causal inference #Clinical study design #Clinical trial #Computer science #Covariate #Econometrics #Mathematics #Medicine #Physical therapy #Randomization #Research design #Restricted randomization #Statistical Methods and Bayesian Inference #Statistical Methods in Clinical Trials #Statistics #stat.ME
paper · pdf · doi:10.1214/08-sts269
published in Statistical Science 23(3) (Institute of Mathematical Statistics) · Published in at http://dx.doi.org/10.1214/08-STS269 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
openalex publication_date 2008/08/01 · arxiv created 2011/02/18 · arxiv updated 2011/02/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
There has been a split in the statistics community about the need for taking covariates into account in the design phase of a clinical trial. There are many advocates of using stratification and covariate-adaptive randomization to promote balance on certain known covariates. However, balance does not always promote efficiency or ensure more patients are assigned to the better treatment. We describe these procedures, including model-based procedures, for incorporating covariates into the design of clinical trials, and give examples where balance, efficiency and ethical considerations may be in conflict. We advocate a new class of procedures, covariate-adjusted response-adaptive (CARA) randomization procedures that attempt to optimize both efficiency and ethical considerations, while maintaining randomization. We review all these procedures, present a few new simulation studies, and conclude with our philosophy.