ArticleFrontiers in public health2021
G-Computation to Causal Mediation Analysis With Sequential Multiple Mediators-Investigating the Vulnerable Time Window of HBV Activity for the Mechanism of HCV Induced Hepatocellular Carcinoma.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 2 citations in OpenAlex.
- Factors Underlying Stroke Recovery Variation by Neighborhood Socioeconomic Status.JAMA network open · 2026Article
- Racial and ethnic disparities in type 2 diabetes: does visceral fat play a role? Evidence from the MESA study.International journal of obesity (2005) · 2026Article
- Racial Disparities of Type 2 Diabetes Through Exercise: The Multi-Ethnic Study of Atherosclerosis.American journal of preventive medicine · 2025Article
- Practical challenges in mediation analysis: a guide for applied researchers.Health services & outcomes research methodology · 2025Article
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Authors and funding
5 authors at 4 institutions in 2 countries.
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Abstract
Regression-based approaches are widely used in causal mediation analysis. The presence of multiple mediators, however, increases the complexity and difficulty of mediation analysis. In such cases, regression-based approaches cannot efficiently address estimation issues. Hence, a flexible approach to mediation analysis is needed. Therefore, we developed a method for using g-computation algorithm to conduct causal mediation analysis in the presence of multiple ordered mediators. Compared to regression-based approaches, the proposed simulation-based approach increases flexibility in the choice of models and increases the range of the outcome scale. The Taiwanese Cohort Study dataset was used to evaluate the efficacy of the proposed approach for investigating the mediating role of early and late HBV viral load in the effect of HCV infection on hepatocellular carcinoma (HCC) in HBV seropositive patients (
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