A Bayesian Hierarchical CACE Model Accounting for Incomplete Noncompliance With Application to a Meta-analysis of Epidural Analgesia on Cesarean Section

Noncompliance with assigned treatments is a common challenge in analyzing and interpreting randomized clinical trials (RCTs). One way to handle noncompliance is to estimate the complier-average causal effect (CACE), the intervention's efficacy in the subpopulation that complies with assigned tr...

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Veröffentlicht in:	Journal of the American Statistical Association 2021, Vol.116 (536), p.1700-1712
Hauptverfasser:	Zhou, Jincheng, Hodges, James S., Chu, Haitao
Format:	Artikel
Sprache:	eng
Schlagworte:	Analgesia Analysis Bayesian analysis Bayesian methods Causal effect Cesarean section Clinical research Clinical trials Data analysis Efficacy Epidural Meta-analysis Missing data Noncompliance Randomized trial Regression analysis Simulation Statistical methods Statistics
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