Publication Date
2021
Journal or Book Title
Contemporary Clinical Trials Communications
Abstract
In group or cluster-randomized trials (GRTs), matching is a technique that can be used to improve covariate balance. When baseline data are available, we suggest a strategy that can be used to achieve the desired balance between treatment and control groups across numerous potential confounding variables. This strategy minimizes the overall within-pair Mahalanobis distance; and involves iteratively: 1) making pairs that minimize the distance between pairs of clusters with respect to potentially confounding variables; 2) visually assessing the potential effects of these pairs and resulting possible randomizations; and 3) reweighting variables of selecting weights to make pairs of clusters. In step 2, we plot the between-arm differences with a parallel-coordinates plot. Investigators can compare plots of different weighting schemes to determine the one that best suits their needs prior to the actual, final, randomization. We demonstrate application of the approach with the Mupirocin-Iodophor Swap Out trial. A webapp is provided.
ORCID
sturdevant, s gwynn/0000-0002-1185-8446
DOI
https://doi.org/10.1016/j.conctc.2021.100746
Volume
22
License
UMass Amherst Open Access Policy
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Funder
National Institutes of Health CommonContemporary FundUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [UH2/UH3 AT007769]
Recommended Citation
Sturdevant, S. Gwynn; Huang, Susan S.; Platt, Richard; and Kleinman, Ken, "Matching in Cluster Randomized Trials Using the Goldilocks Approach" (2021). Biostatistics and Epidemiology Faculty Publications Series.
22
https://doi.org/10.1016/j.conctc.2021.100746