<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Cai J</submitter><funding>the National Natural Science Foundation of China</funding><pagination>20</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12857073</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>26(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Cluster randomized trials (CRTs) require balanced baseline covariates to yield unbiased estimates of treatment effects. Existing approaches such as constrained randomization can improve balance but may compromise allocation randomness. We introduce Cluster Minimal Sufficient Balance (CMSB), a cluster randomization method designed to enhance covariate balance while preserving allocation randomness and computational efficiency.&lt;h4>Methods&lt;/h4>CMSB integrates dynamic imbalance monitoring with conditional biased randomization into a single procedure. The method accommodates both continuous and categorical covariates and was evaluated through simulation studies comparing its performance with constrained randomization, simple randomization, block randomization, stratified rand</pubmed_abstract><journal>BMC medical research methodology</journal><pubmed_title>Cluster minimal sufficient balance (CMSB): an efficient covariate balancing randomization method for cluster randomized trials.</pubmed_title><pmcid>PMC12857073</pmcid><funding_grant_id>82473732</funding_grant_id><funding_grant_id>82322060</funding_grant_id><pubmed_authors>Shao F</pubmed_authors><pubmed_authors>Li C</pubmed_authors><pubmed_authors>Zeng L</pubmed_authors><pubmed_authors>Cai J</pubmed_authors><pubmed_authors>Suo S</pubmed_authors><pubmed_authors>Khairallah C</pubmed_authors><pubmed_authors>Zhang B</pubmed_authors><pubmed_authors>Yan H</pubmed_authors><pubmed_authors>Ndip V</pubmed_authors><pubmed_authors>Chen T</pubmed_authors></additional><is_claimable>false</is_claimable><name>Cluster minimal sufficient balance (CMSB): an efficient covariate balancing randomization method for cluster randomized trials.</name><description>&lt;h4>Background&lt;/h4>Cluster randomized trials (CRTs) require balanced baseline covariates to yield unbiased estimates of treatment effects. Existing approaches such as constrained randomization can improve balance but may compromise allocation randomness. We introduce Cluster Minimal Sufficient Balance (CMSB), a cluster randomization method designed to enhance covariate balance while preserving allocation randomness and computational efficiency.&lt;h4>Methods&lt;/h4>CMSB integrates dynamic imbalance monitoring with conditional biased randomization into a single procedure. The method accommodates both continuous and categorical covariates and was evaluated through simulation studies comparing its performance with constrained randomization, simple randomization, block randomization, stratified rand</description><dates><release>2026-01-01T00:00:00Z</release><publication>2026 Jan</publication><modification>2026-06-17T07:04:48.644Z</modification><creation>2026-06-17T03:10:39.852Z</creation></dates><accession>S-EPMC12857073</accession><cross_references><pubmed>41484830</pubmed><doi>10.1186/s12874-025-02758-0</doi></cross_references></HashMap>