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Comment
. 2019 Jul 1;188(7):1204-1205.
doi: 10.1093/aje/kwy281.

Counterpoint: Mediation Formulas With Binary Mediators and Outcomes and the "Rare Outcome Assumption"

Tyler J VanderWeele  1 , Linda Valeri  2 , Cande V Ananth  3   4
Affiliations
Comment

Counterpoint: Mediation Formulas With Binary Mediators and Outcomes and the "Rare Outcome Assumption"

Tyler J VanderWeele et al. Am J Epidemiol. .

Abstract

In their accompanying article, Samoilenko and Lefebvre (Am J Epidemiol. 2019;188(7):1203-1205) correctly note 2 typographical errors in the formulas presented in a 2011 paper on placental abruption by Ananth and VanderWeele (Am J Epidemiol. 2011;174(1):99-108). Fortunately, to the best of our knowledge, researchers are using our methods papers and Dr. VanderWeele's 2015 book on mediation analysis (Explanation in Causal Inference; Oxford University Press, New York, New York), rather than the paper on placental abruption, to carry out their direct and indirect effect analyses; and in our methods papers and the book, the formulas are correct. The formulas discussed by Samoilenko and Lefebvre and in our work make reference to a "rare outcome assumption." In evaluating this assumption, it is important to note that the outcome is to be relatively rare across all strata defined by the exposure and the mediator-a point that is often neglected.

Keywords: direct and indirect effects; mediation; odds ratios; rare outcomes.

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References

    1. Samoilenko M, Lefebvre G. Point: risk ratio equations for natural direct and indirect effects in causal mediation analysis of a binary mediator and a binary outcome—a fresh look at the formulas. Am J Epidemiol. 2019;188(7):1201–1203. - PubMed
    1. Ananth CV, VanderWeele TJ. Placental abruption and perinatal mortality with preterm delivery as a mediator: disentangling direct and indirect effects. Am J Epidemiol. 2011;174(1):99–108. - PMC - PubMed
    1. Valeri L, Vanderweele TJ. Mediation analysis allowing for exposure-mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros. Psychol Methods. 2013;18(2):137–150. - PMC - PubMed
    1. VanderWeele TJ. Explanation in Causal Inference: Methods for Mediation and Interaction. New York, NY: Oxford University Press; 2015.
    1. American Psychological Association Supplemental material for mediation analysis allowing for exposure–mediator interactions and causal interpretation: theoretical assumptions and implementation with SAS and SPSS macros. http://supp.apa.org/psycarticles/supplemental/a0031034/a0031034_supp.html. Accessed December 4, 2018. - PMC - PubMed

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