A new method for clustered survival data: Estimation of treatment effect heterogeneity and variable selection
Description
We recently developed a new method random-intercept accelerated failure time model with Bayesian additive regression trees (riAFT-BART) to draw causal inferences about population treatment effect on patient survival from clustered and censored