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.
