Semiparametric Transformation Models for Causal Inference in Time-to-Event Studies with All-or-Nothing Compliance
完全依从或完全不依从生存研究中的因果推断：半参数变换模型
Summary We consider causal inference in randomized survival studies with right-censored outcomes and all-or-nothing compliance, using semiparametric transformation models to estimate the distribution of survival times in treatment and control groups, conditionally on covariates and latent compliance type. Estimands depending on these distributions, e.g. the complier average causal effect, the complier effect on survival beyond time t and the complier quantile effect, are…