Bayesian hierarchical bootstrap framework for causal subgroup estimation with a time-to-event outcome
事件时间结果因果亚组估计的贝叶斯层级自助框架
Causal estimation of treatment effects within prespecified subgroups, such as biomarker-defined strata, disease phenotypes, or demographic groups are often of clinical interest. Bayesian approaches are attractive for subgroup effect estimation because flexible priors can represent complex treatment heterogeneity and propagate posterior uncertainty. Frequentist methods for prespecified causal subgroup analysis with time-to-event outcomes are also available, including…