5 papers
Proximal Mediation Analysis with Unmeasured Treatment-Induced Confounding
Xiaoying Zhang, Jiawei Shan, Wei Li
Mediation analysis provides a central framework for elucidating causal mechanisms, yet its application is often impeded by treatment-induced confounding, under which the widely use…
Beyond Exchangeability: Distribution-Shift-Aware Integration of External Control Data in Randomized Trials
Jiawei Shan, Yiteng Tu, Guanbo Wang +2
Randomized controlled trials (RCTs) are the gold standard for evaluating causal effects but are often costly and difficult to scale; consequently, they are frequently augmented wit…
Efficient Estimation of Average Treatment Effect on the Treated under Endogenous Treatment Assignment
Trinetri Ghosh, Jiawei Shan, Menggang Yu +1
In this paper, we consider estimation of average treatment effect on the treated (ATT), an interpretable and relevant causal estimand to policy makers when treatment assignment is…
Efficient estimation of average treatment effects with unmeasured confounding and proxies
Chunrong Ai, Jiawei Shan
Proximal causal inference provides a framework for estimating the average treatment effect (ATE) in the presence of unmeasured confounding by leveraging outcome and treatment proxi…
Efficient Nonparametric Inference for Mediation Analysis with Nonignorable Missing Confounders
Jiawei Shan, Wei Li, Chunrong Ai
Mediation analysis is widely used for exploring treatment mechanisms; however, it faces challenges when nonignorable missing confounders are present. Efficient inference of mediati…