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.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.AP 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.