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Identification and Bounding of Central Moments of Causal Effects Using Marginal Moments Information
Naoya Hashimoto, Yuta Kawakami, Jin Tian
Evaluating the causal effect of a treatment on an outcome is a central objective in causal inference. While the average causal effect summarizes the mean impact of treatment, the c…
Cumulative Natural Direct and Indirect Effects for Causal Mediation Analysis
Yuta Kawakami, Jin Tian
Causal mediation analysis provides a fundamental framework for quantifying the contributions of different pathways from a treatment to an outcome through a mediator. The na…
Measures for Assessing Causal Effect Heterogeneity Unexplained by Covariates
Yuta Kawakami, Jin Tian
There has been considerable interest in estimating heterogeneous causal effects across individuals or subpopulations. Researchers often assess causal effect heterogeneity based on…
Decomposition of Probabilities of Causation with Two Mediators
Yuta Kawakami, Jin Tian
Mediation analysis for probabilities of causation (PoC) provides a fundamental framework for evaluating the necessity and sufficiency of treatment in provoking an event through dif…
Moments of Causal Effects
Yuta Kawakami, Jin Tian
The moments of random variables are fundamental statistical measures for characterizing the shape of a probability distribution, encompassing metrics such as mean, variance, skewne…