A Bayesian Nonparametric Approach for Evaluating the Effect of Treatment in Randomized Trials with Semi-Competing Risks

03/20/2019

∙

by   Yanxun Xu, et al.

∙

0

∙

share

We develop a Bayesian nonparametric (BNP) approach to evaluate the effect of treatment in a randomized trial where a nonterminal event may be censored by a terminal event, but not vice versa (i.e., semi-competing risks). Based on the idea of principal stratification, we define a novel estimand for the causal effect of treatment on the non-terminal event. We introduce identification assumptions, indexed by a sensitivity parameter, and show how to draw inference using our BNP approach. We conduct a simulation study and illustrate our methodology using data from a brain cancer trial.