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.
b) For individuals in clusters such thatS (m) i =k, sample from Y mis(m) ij ∼N(X mis ij B(m) k +ϕ Y(m) i , σ2(m) 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.