3 papers
stat.ME2026
The Promises of Multiple Experiments: Identifying Joint Distribution of Potential Outcomes
Peng Wu, Xiaojie Mao
Typical causal effects are defined based on the marginal distribution of potential outcomes. However, many real-world applications require causal estimands involving the joint dist…
stat.OT2026
A Distributional Perspective on Pearl's Causal Hierarchy: From Marginal to Joint and Individualized Potential Outcomes
Peng Wu, Linbo Wang
Pearl's causal hierarchy is a foundational lens for formulating causal questions and is most often discussed within the framework of structural causal models. We recast the hierarc…
stat.ME2025
Adaptive Data-Borrowing for Improving Treatment Effect Estimation using External Controls
Qinwei Yang, Jingyi Li, Peng Wu
Randomized controlled trials (RCTs) often exhibit limited inferential efficiency in estimating treatment effects due to small sample sizes. In recent years, the combination of exte…