A BAYESIAN MACHINE LEARNING APPROACH FOR ESTIMATING HETEROGENEOUS SURVIVOR CAUSAL EFFECTS: APPLICATIONS TO A CRITICAL CARE TRIAL

• Published in: The annals of applied statistics Vol. 18; no. 1; p. 350
• Main Authors: Chen, Xinyuan, Harhay, Michael O, Tong, Guangyu, Li, Fan
• Format: Journal Article
• Language: English
• Published: United States 01.03.2024
• Subjects: Acute lung injury; truncation by death; Bayesian additive regression trees; principal stratification; causal inference; heterogeneity of treatment effects

Assessing heterogeneity in the effects of treatments has become increasingly popular in the field of causal inference and carries important implications for clinical decision-making. While extensive literature exists for studying treatment effect heterogeneity when outcomes are fully observed, there...