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Effect Measure Modification by Covariates in Mediation: Extending Regression-Based Causal Mediation Analysis

Author

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  • Li, Yi

    (Brigham and Women's Hospital)

  • Mathur, Maya B
  • Solomon, Daniel
  • Glynn, Robert J.
  • Yoshida, Kazuki

Abstract

In this paper, we generalize the closed-form regression-based mediation analysis approach proposed by Valeri and VanderWeele (2013, 2015) to accommodate effect measure modification by the covariates. We show that covariate levels can affect the presence and magnitude of EMM of the conditional NDE and NIE, and that the dependence of the NDE and NIE depend on covariates is affected by the link functions of mediator and outcome models as well as the strength of EMM and of exposure-mediator interaction. Our proposed approach is implemented in R package regmedint (version 1.0.0), available at https://cran.r-project.org/web/packages/regmedint/index.html.

Suggested Citation

  • Li, Yi & Mathur, Maya B & Solomon, Daniel & Glynn, Robert J. & Yoshida, Kazuki, 2022. "Effect Measure Modification by Covariates in Mediation: Extending Regression-Based Causal Mediation Analysis," OSF Preprints 3gf64, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:3gf64
    DOI: 10.31219/osf.io/3gf64
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    1. Li, Yi & Mathur, Maya B & Yoshida, Kazuki, 2022. "R package regmedint: extension of regression-based causal mediation analysis with effect measure modification by covariates," OSF Preprints d4brv, Center for Open Science.
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