2 citations · 2 across the 11 of their papers we have counts for
11 papers
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…
Fixed-Confidence Best-Arm Identification for Causal Mediation Analysis
Harsh Shrivastava, Yuta Kawakami, Junpei Komiyama +1
This paper studies the problem of identifying the treatment that maximizes the expected natural direct potential outcome (NDPO), which captures the potential outcome of an interven…
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…
Bounds and Identification of Joint Probabilities of Potential Outcomes and Observed Variables under Monotonicity Assumptions
Naoya Hashimoto, Yuta Kawakami, Jin Tian
Evaluating joint probabilities of potential outcomes and observed variables, and their linear combinations, is a fundamental challenge in causal inference. This paper addresses the…
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…
Potential Outcome Rankings for Counterfactual Decision Making
Yuta Kawakami, Jin Tian
Counterfactual decision-making in the face of uncertainty involves selecting the optimal action from several alternatives using causal reasoning. Decision-makers often rank expecte…
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…
Mediation Analysis for Probabilities of Causation
Yuta Kawakami, Jin Tian
Probabilities of causation (PoC) offer valuable insights for informed decision-making. This paper introduces novel variants of PoC-controlled direct, natural direct, and natural in…
Probabilities of Causation for Continuous and Vector Variables
Yuta Kawakami, Manabu Kuroki, Jin Tian
Probabilities of causation (PoC) are valuable concepts for explainable artificial intelligence and practical decision-making. PoC are originally defined for scalar binary variables…
Identification and Estimation of Conditional Average Partial Causal Effects via Instrumental Variable
Yuta Kawakami, Manabu Kuroki, Jin Tian
There has been considerable recent interest in estimating heterogeneous causal effects. In this paper, we study conditional average partial causal effects (CAPCE) to reveal the het…