collaborators

6 papers

stat.ME2026

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…

stat.ME2026

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…

stat.ME2026

Identifying Causal Effects Using Instrumental Variables from the Auxiliary Dataset

Kang Shuai, Shanshan Luo, Wei Li +1

Instrumental variable approaches have gained popularity for estimating causal effects in the presence of unmeasured confounders. However, the availability of instrumental variables…

stat.AP2026

Assessing Interactive Causes of an Occurred Outcome Due to Two Binary Exposures

Shanshan Luo, Wei Li, Xueli Wang +2

In contrast to evaluating treatment effects, causal attribution analysis focuses on identifying the key factors responsible for an observed outcome. For two binary exposure variabl…

stat.ME2025

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…

stat.ME2025

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…