ArticleThe international journal of biostatistics2011
A complete graphical criterion for the adjustment formula in mediation analysis.
Article in The international journal of biostatistics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Simple graphical rules for assessing selection bias in general-population and selected-sample treatment effects.American journal of epidemiology · 2025Article
- Mediating mechanisms of the relationship between exposure to deprivation and threat during childhood and adolescent psychopathology: evidence from the Millennium Cohort Study.European child & adolescent psychiatry · 2024Article
- The Covid-19 pandemic as an accelerator of economic worries and labor-related mental health polarization in Germany? A longitudinal interacted mediation analysis with a difference-in-difference comparison.SSM - population health · 2023Article
- Youth organizations, social mobility and health in middle age: evidence from a Scottish 1950s prospective cohort study.European journal of public health · 2023Article
- CAUSAL MEDIATION ANALYSIS FOR SPARSE AND IRREGULAR LONGITUDINAL DATA.The annals of applied statistics · 2021Article
- Genetic nurturing, missing heritability, and causal analysis in genetic statistics.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Sensitivity analysis for mistakenly adjusting for mediators in estimating total effect in observational studies.BMJ open · 2017Article
- Mediation analysis with time varying exposures and mediators.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2017Article
- Endogenous Selection Bias: The Problem of Conditioning on a Collider Variable.Annual review of sociology · 2014Article
- Sensitivity analysis for direct and indirect effects in the presence of exposure-induced mediator-outcome confounders.Epidemiology, biostatistics and public health · 2014Article
- Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros.Psychological methods · 2013Article
- Estimation of mediation effects for zero-inflated regression models.Statistics in medicine · 2012Article
- Combining directed acyclic graphs and the change-in-estimate procedure as a novel approach to adjustment-variable selection in epidemiology.BMC medical research methodology · 2012Article
- The causal mediation formula--a guide to the assessment of pathways and mechanisms.Prevention science : the official journal of the Society for Prevention Research · 2012Article
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2 authors.
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Abstract
Various assumptions have been used in the literature to identify natural direct and indirect effects in mediation analysis. These effects are of interest because they allow for effect decomposition of a total effect into a direct and indirect effect even in the presence of interactions or non-linear models. In this paper, we consider the relation and interpretation of various identification assumptions in terms of causal diagrams interpreted as a set of non-parametric structural equations. We show that for such causal diagrams, two sets of assumptions for identification that have been described in the literature are in fact equivalent in the sense that if either set of assumptions holds for all models inducing a particular causal diagram, then the other set of assumptions will also hold for all models inducing that diagram. We moreover build on prior work concerning a complete graphical identification criterion for covariate adjustment for total effects to provide a complete graphical criterion for using covariate adjustment to identify natural direct and indirect effects. Finally, we show that this criterion is equivalent to the two sets of independence assumptions used previously for mediation analysis.
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