4 papers
General sample size analysis for probabilities of causation: a delta method approach
Tianyuan Cheng, Ruirui Mao, Judea Pearl +1
Probabilities of causation (PoCs), such as the probability of necessity and sufficiency (PNS), are important tools for decision making but are generally not point identifiable. Exi…
Bounding Probabilities of Causation with Partial Causal Diagrams
Yuxuan Xie, Ang Li
Probabilities of causation are fundamental to individual-level explanation and decision making, yet they are inherently counterfactual and not point-identifiable from data in gener…
Recover Experimental Data with Selection Bias using Counterfactual Logic
Jingyang He, Shuai Wang, Ang Li
Selection bias, arising from the systematic inclusion or exclusion of certain samples, poses a significant challenge to the validity of causal inference. While Bareinboim et al. in…
Estimating Probabilities of Causation with Machine Learning Models
Shuai Wang, Ang Li
Probabilities of causation play a crucial role in modern decision-making. This paper addresses the challenge of predicting probabilities of causation for subpopulations with insuff…