3 papers
math.ST2024
Identifying and bounding the probability of necessity for causes of effects with ordinal outcomes
Chao Zhang, Zhi Geng, Wei Li +1
Although the existing causal inference literature focuses on the forward-looking perspective by estimating effects of causes, the backward-looking perspective can provide insights…
stat.ME2024
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…
stat.ME2024
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…