Estimating Heterogeneous Causal Mediation Effects with Bayesian Decision Tree Ensembles
用贝叶斯决策树集成估计异质性因果中介效应
The causal inference literature has increasingly recognized that targeting treatment effect heterogeneity can lead to improved scientific understanding and policy recommendations. Similarly, studying the causal pathway connecting the treatment to the outcome can be useful. We address these problems in the context of causal mediation analysis . We introduce a varying coefficient model based on Bayesian additive regression trees to estimate and regularize heterogeneous causal…