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Common scale minimal sufficient balance: An improved method for covariate‐adaptive randomization based on the Wilcoxon‐Mann‐Whitney odds ratio statistic
Author(s) -
Johns Hannah,
Italiano Dominic,
Campbell Bruce,
Churilov Leonid
Publication year - 2022
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.9332
Subject(s) - covariate , statistics , wilcoxon signed rank test , type i and type ii errors , mathematics , statistic , econometrics , randomization , scale (ratio) , balance (ability) , computer science , randomized controlled trial , mann–whitney u test , medicine , physics , surgery , quantum mechanics , physical medicine and rehabilitation
Minimal sufficient balance (MSB) is a recently suggested method for adaptively controlling covariate imbalance in randomized controlled trials in a manner which reduces the impact on randomness of allocation over other approaches by only intervening when the imbalance is sufficiently significant. Despite its improvements, the approach is unable to consider the relative clinical importance or magnitude of imbalance in each covariate weight, and ignores any imbalance which is not statistically significant, even when these imbalances may collectively justify intervention. We propose the common scale MSB (CS‐MSB) method which addresses these limitations, and present simulation studies comparing our proposed method to MSB. We demonstrate that CS‐MSB requires less intervention than MSB to achieve the same level of covariate balance, and does not adversely impact either statistical power or Type‐I error.