7 papers
Identification and Inference for Structural Accelerated Failure Time Models via Instrument Interactions
Qiushi Bu, Wen Su, Xinyu Zhang +2
We study causal inference for time-to-event outcomes under right censoring in the presence of unmeasured confounding. Focusing on structural accelerated failure time models, we dev…
Flexible semiparametric modeling with application to Causal Inference
Kun Ren, Wen Su, Li Liu +2
This paper proposes a flexible new framework for constructing Neyman-orthogonal scores in semiparametric models involving infinite-dimensional nuisance parameters. While locally es…
Learning Optimal Distributionally Robust Individualized Treatment Rules Integrating Multi-Source Data
Wenhai Cui, Wen Su, Xingqiu Zhao
Integrative analysis of multiple datasets for estimating optimal individualized treatment rules (ITRs) can enhance decision efficiency. A central challenge is posterior shift, wher…
Learning Optimal Individualized Decision Rules with Conditional Demographic Parity
Wenhai Cui, Wen Su, Donglin Zeng +1
Individualized decision rules (IDRs) have become increasingly prevalent in societal applications such as personalized marketing, healthcare, and public policy design. However, a cr…
Semiparametric Causal Inference for Right-Censored Outcomes with Many Weak Invalid Instruments
Qiushi Bu, Wen Su, Xingqiu Zhao +1
We propose a semiparametric framework for causal inference with right-censored survival outcomes and many weak invalid instruments, motivated by Mendelian randomization in biobank…
Optimal Transport Learning: Balancing Value Optimization and Fairness in Individualized Treatment Rules
Wenhai Cui, Xiaoting Ji, Wen Su +2
Individualized treatment rules (ITRs) have gained significant attention due to their wide-ranging applications in fields such as precision medicine, ridesharing, and advertising re…