causalBETA: An R Package for Bayesian Semiparametric Causal Inference with Event-Time Outcomes
causalBETA:事件时间结局的贝叶斯半参数因果推断 R 包
Observational studies are often conducted to estimate causal effects of treatments or exposures on event-time outcomes. Since treatments are not randomized in observational studies, techniques from causal inference are required to adjust for confounding. Bayesian approaches to causal estimates are desirable because they provide 1) prior smoothing provides useful regularization of causal effect estimates, 2) flexible models that are robust to misspecification, 3) full…