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stat.ME2024
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Lucile Ter-Minassian, Liran Szlak, Ehud Karavani +2
Interpretability and transparency are essential for incorporating causal effect models from observational data into policy decision-making. They can provide trust for the model in…
stat.ME2018
Benchmarking Framework for Performance-Evaluation of Causal Inference Analysis
Yishai Shimoni, Chen Yanover, Ehud Karavani +1
Causal inference analysis is the estimation of the effects of actions on outcomes. In the context of healthcare data this means estimating the outcome of counter-factual treatments…