Bayesian Sensitivity Analysis for Causal Estimation with Time-varying Unmeasured Confounding
时变未测量混杂下因果估计的贝叶斯敏感性分析
Causal inference relies on the untestable assumption of no unmeasured confounding. Sensitivity analysis can be used to quantify the impact of unmeasured confounding on causal estimates. Among sensitivity analysis methods proposed in the literature for unmeasured confounding, the latent confounder approach is favoured for its intuitive interpretation via the use of bias parameters to specify the relationship between the observed and unobserved variables and the sensitivity…