Reweighted Mahalanobis Distance Matching for Cluster Randomized Trials with Missing Data

摘要

PurposeThis paper introduces an improved tool for designing matched-pairs randomized trials. The tool allows the incorporation of clinical and other knowledge regarding the relative importance of variables used in matching and allows for multiple types of missing data. The method is illustrated in the context of a cluster-randomized trial. A web application and R package are introduced to implement the method and incorporate recent advances in the area.