Journal
STATISTICS IN MEDICINE
Volume 32, Issue 19, Pages 3357-3372Publisher
WILEY
DOI: 10.1002/sim.5795
Keywords
cluster randomized trial; Monte-Carlo simulations; selection bias; propensity score
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Funding
- French Agence Nationale de la Recherche [ANR-2010-PRSP-010-01]
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Cluster randomized trials (CRTs) are often prone to selection bias despite randomization. Using a simulation study, we investigated the use of propensity score (PS) based methods in estimating treatment effects in CRTs with selection bias when the outcome is quantitative. Of four PS-based methods (adjustment on PS, inverse weighting, stratification, and optimal full matching method), three successfully corrected the bias, as did an approach using classical multivariable regression. However, they showed poorer statistical efficiency than classical methods, with higher standard error for the treatment effect, and typeI error much smaller than the 5% nominal level. Copyright (c) 2013 John Wiley & Sons, Ltd.
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