4 papers
Sequential Treatment Effect Estimation with Unmeasured Confounders
Yingrong Wang, Anpeng Wu, Baohong Li +4
This paper studies the cumulative causal effects of sequential treatments in the presence of unmeasured confounders. It is a critical issue in sequential decision-making scenarios…
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
Anpeng Wu, Kun Kuang, Ruoxuan Xiong +4
In causal inference, encouragement designs (EDs) are widely used to analyze causal effects, when randomized controlled trials (RCTs) are impractical or compliance to treatment cann…
Causal Inference with Complex Treatments: A Survey
Yingrong Wang, Haoxuan Li, Minqin Zhu +4
Causal inference plays an important role in explanatory analysis and decision making across various fields like statistics, marketing, health care, and education. Its main task is…
Semiparametric Estimation of Treatment Effects in Observational Studies with Heterogeneous Partial Interference
Zhaonan Qu, Ruoxuan Xiong, Jizhou Liu +1
In many observational studies in social science and medicine, subjects or units are connected, and one unit's treatment and attributes may affect another's treatment and outcome, v…