ArticleStatistics in medicine2020
Statistical properties of minimal sufficient balance and minimization as methods for controlling baseline covariate imbalance at the design stage of sequential clinical trials.
Article in Statistics in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Minimization of expected balance distribution differences: optimization of the randomized allocation algorithm based on the Pocock-Simon design.BMC medical research methodology · 2026Article
- Comments on Randomized Trial of Intestinal Obstruction Catheter Combined with Modified Dachengqi Decoction [Letter].International journal of general medicine · 2026Article
- Workflows to automate covariate-adaptive randomization in REDCap via data entry triggers.JAMIA open · 2025Article
- Strategies to boost statistical efficiency in randomized oncology trials with primary time-to-event endpoints.Statistical methods in medical research · 2025Article
- Common scale minimal sufficient balance: An improved method for covariate-adaptive randomization based on the Wilcoxon-Mann-Whitney odds ratio statistic.Statistics in medicine · 2022Article
- Impact of minimal sufficient balance, minimization, and stratified permuted blocks on bias and power in the estimation of treatment effect in sequential clinical trials with a binary endpoint.Statistical methods in medical research · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
When the number of baseline covariates whose imbalance needs to be controlled in a sequential randomized controlled trial is large, minimization is the most commonly used method for randomizing treatment assignments. The lack of allocation randomness associated with the minimization method has been the source of controversy, and the need to reduce even minor imbalances inherent in the minimization method has been challenged. The minimal sufficient balance (MSB) method is an alternative to the minimization method. It prevents serious imbalance from a large number of covariates while maintaining a high level of allocation randomness. In this study, the two treatment allocation methods are compared with regards to the effectiveness of balancing covariates across treatment arms and allocation randomness in equal allocation clinical trials. The MSB method proves to be equal or superior in both respects. In addition, type I error rate is preserved in analyses for both balancing methods, when using a binary endpoint.
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Registered trials
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