Develops a Bayesian framework using latent mixture models to estimate ITT and CACE effects in cluster randomized trials while accounting for partial cluster implementation and individual noncompliance.
Without loss of generality, assume thatW i = 0andS (m) i =k
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A Bayesian Framework for Latent Compliance Modeling in Cluster Randomized Trials with One-Sided Noncompliance
Develops a Bayesian framework using latent mixture models to estimate ITT and CACE effects in cluster randomized trials while accounting for partial cluster implementation and individual noncompliance.