7 papers · 1 filter
Probability of Root Cause: A Counterfactual Definition and Its Identification
Zitong Lu, Zhi Geng, Wei Li +1
Attributing an observed outcome to its root cause is a central task in domains ranging from medical diagnosis to engineering fault diagnosis. Existing approaches either equate the…
Identification and estimation of causal peer effects using instrumental variables
Shanshan Luo, Kang Shuai, Yechi Zhang +2
In social science researches, causal inference regarding peer effects often faces significant challenges due to homophily bias and contextual confounding. For example, unmeasured h…
Causal Inference with Outcomes Truncated by Death and Missing Not at Random
Wei Li, Yuan Liu, Shanshan Luo +1
In clinical trials, principal stratification analysis is commonly employed to address the issue of truncation by death, where a subject dies before the outcome can be measured. How…
Efficiency-improved doubly robust estimation with non-confounding predictive covariates
Shanshan Luo, Mengchen Shi, Wei Li +2
In observational studies, covariates with substantial missing data are often omitted, despite their strong predictive capabilities. These excluded covariates are generally believed…
Mediation analysis with unmeasured confounding between parallel mediators and outcome
Kang Shuai, Lan Liu, Yangbo He +1
Mediation analysis extending beyond single mediators has gained significant attention in recent years. However, related methods often assume the absence of unmeasured mediator-outc…
Multiply robust estimation of causal effects using linked data
Shanshan Luo, Yechi Zhang, Wei Li
Unmeasured confounding presents a common challenge in observational studies, potentially making standard causal parameters unidentifiable without additional assumptions. Given the…