Bayesian Graphical Models, Intention-to-Treat, and the Rubin Causal Model
Proceedings of the Seventh International Workshop on Artificial Intelligence and Statistics, PMLR R2, 1999.
In clinical trials with significant noncompliance the standard intention-to-treat analyses sometimes mislead. Rubin’s causal model provides an alternative method of analysis that can shed extra light on clinical trial data. Formulating the Rubin Causal Model as a Bayesian graphical model facilitates model communication and computation.