2 papers
stat.ME2026
Quantifying Individual Risk for Binary Outcomes
Peng Wu, Peng Ding, Zhi Geng +1
Understanding treatment effect heterogeneity is crucial for reliable decision-making in treatment evaluation and selection. The conditional average treatment effect (CATE) is widel…
stat.ME2025
Identification and multiply robust estimation of causal effects via instrumental variables from an auxiliary population
Wei Li, Jiapeng Liu, Peng Ding +1
Estimating causal effects in a target population with unmeasured confounders is challenging, especially when instrumental variables (IVs) are unavailable. However, IVs from auxilia…