Cluster minimal sufficient balance (CMSB): an efficient covariate balancing randomization method for cluster randomized trials
CMSB effectively balances the competing demands of covariate balance, allocation randomness, and computational efficiency in cluster randomized trials. Its ability to handle high-dimensional covariates makes it particularly suitable for large-scale trials.
Authors
- Jiaxin Cai (ORCID: https://orcid.org/0000-0003-3861-1969)
- Binyan Zhang (ORCID: https://orcid.org/0000-0001-6307-9623)
- Shanshan Suo
- Carole Khairallah
- Fang Shao (ORCID: https://orcid.org/0000-0002-2551-2956)
- Chao Li (ORCID: https://orcid.org/0000-0002-4337-303X)
- Valirie Agbor Ndip
- Tao Chen
- Lingxia Zeng
- Hong Yan
Institutions
- Shanxi University (CN)
- Liverpool School of Tropical Medicine (GB)
- Xi'an Medical University (CN)
- Nanjing Medical University (CN)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- BMC Medical Research Methodology
- Published
- 2026-01-02
- DOI
- https://doi.org/10.1186/s12874-025-02758-0
- Primary Topic
- Bayesian Methods and Mixture Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00