ArticleClinical trials (London, England)2023
Covariate-constrained randomization with cluster selection and substitution.
Article in Clinical trials (London, England), 2023. 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.
- Randomized Trial of Targeted Indoor Spraying to Prevent Aedes-Borne Diseases.The New England journal of medicine · 2025Trial
- Cluster minimal sufficient balance (CMSB): an efficient covariate balancing randomization method for cluster randomized trials.BMC medical research methodology · 2026Article
- Analysis methods for covariate-constrained cluster randomized trials with time-to-event outcomes.BMC medical research methodology · 2025Article
- Evidence of Ongoing Transmission of Zika Virus in Mérida, Mexico.The American journal of tropical medicine and hygiene · 2024Article
- Article
- Targeted indoor residual insecticide applications shift Aedes aegypti age structure and arbovirus transmission potential.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundAn ongoing cluster-randomized trial for the prevention of arboviral diseases utilizes covariate-constrained randomization to balance two treatment arms across four specified covariates and geographic sector. Each cluster is within a census tract of the city of Mérida, Mexico, and there were 133 eligible tracts from which to select 50. As some selected clusters may have been subsequently found unsuitable in the field, we desired a strategy to substitute new clusters while maintaining covariate balance.
methodsWe developed an algorithm that successfully identified a subset of clusters that maximized the average minimum pairwise distance between clusters in order to reduce contamination and balanced the specified covariates both before and after substitutions were made. SIMULATIONS: Simulations were performed to explore some limitations of this algorithm. The number of selected clusters and eligible clusters were varied along with the method of selecting the final allocation pattern.
conclusionThe algorithm is presented here as a series of optional steps that can be added to the standard covariate-constrained randomization process in order to achieve spatial dispersion, cluster subsampling, and cluster substitution. Simulation results indicate that these extensions can be used without loss of statistical validity, given a sufficient number of clusters included in the trial.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.