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Mediation Analysis with Multiple Mediators
Open accessAbstract
Recent advances in the causal inference literature on mediation have extended traditional approaches to direct and indirect effects to settings that allow for interactions and non-linearities. In this paper, these approaches from causal inference are further extended to settings in which multiple mediators may be of interest. Two analytic approaches, one based on regression and one based on weighting are proposed to estimate the effect mediated through multiple mediators and the effects through other pathways. The approaches proposed here accommodate exposure-mediator interactions and, to a certain extent, mediator-mediator interactions as well. The methods handle binary or continuous mediators and binary, continuous or count outcomes. When the mediators affect one another, the strategy of trying to assess direct and indirect effects one mediator at a time will in general fail; the approach given in this paper can still be used. A characterization is moreover given as to when the sum of the mediated effects for multiple mediators considered separately will be equal to the mediated effect of all of the mediators considered jointly. The approach proposed in this paper is robust to unmeasured common causes of two or more mediators.
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“We conducted causal mediation analysis (CMA) with cortisol suppression (CS) by dexamethasone (DEX) as an exposure variable, HOMA-IR, hs-CRP, hypoxanthine, and GGT as the joint mediators, and metabolites as dependent variables while controlling for covariates (80).”
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“This observation is possible and could be due to 3 factors: (1) mediators affecting one another, (2) interaction between mediators affecting the outcome, or (3) other mediators with a”
From Mindful attention is inversely associated with pain via mediation by psychological distress in orthopedic patients. (2024) · cites this paper as [52]
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Metadata
- Authors
- VanderWeele, T., & Vansteelandt, S.
- Affiliations
- Harvard University (US)
- Ghent University (BE)
- Corresponding author
- VanderWeele, Tyler
- Venue
- Epidemiologic Methods
- Publisher
- Walter de Gruyter GmbH
- Published
- 2014-01-03
- Volume
- 2
- Issue
- 1
- Pages
- 95-115
- ISSN
- 2161-962X (ISSN-L)
- 2194-9263
- PMC
- PMC4287269
- OpenAlex
- W2009754435
- Cited by
- 858
- References
- 23
- Citations by year
- 2026: 62 · 2025: 96 · 2024: 140 · 2023: 97 · 2022: 106 · 2021: 95 · 2020: 85 · 2019: 64 · 2018: 40 · 2017: 39 · 2016: 16 · 2015: 13 · 2014: 4
- FWCI
- 25.37
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Epidemiologic Methods (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Ghent University Academic Bibliography (Ghent University) (submittedVersion)
- Funders
- National Institute of Environmental Health Sciences (R01ES017876)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
- Keywords
- mediation analysis, multiple mediators, direct and indirect effects, count outcomes, causal inference, regression estimation
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