Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2010 Dec 15;172(12):1339-48.
doi: 10.1093/aje/kwq332. Epub 2010 Oct 29.

Odds ratios for mediation analysis for a dichotomous outcome

Affiliations

Odds ratios for mediation analysis for a dichotomous outcome

Tyler J Vanderweele et al. Am J Epidemiol. .

Abstract

For dichotomous outcomes, the authors discuss when the standard approaches to mediation analysis used in epidemiology and the social sciences are valid, and they provide alternative mediation analysis techniques when the standard approaches will not work. They extend definitions of controlled direct effects and natural direct and indirect effects from the risk difference scale to the odds ratio scale. A simple technique to estimate direct and indirect effect odds ratios by combining logistic and linear regressions is described that applies when the outcome is rare and the mediator continuous. Further discussion is given as to how this mediation analysis technique can be extended to settings in which data come from a case-control study design. For the standard mediation analysis techniques used in the epidemiologic and social science literatures to be valid, an assumption of no interaction between the effects of the exposure and the mediator on the outcome is needed. The approach presented here, however, will apply even when there are interactions between the effect of the exposure and the mediator on the outcome.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Example of mediation with exposure A, mediator M, outcome Y, and covariates C.
Figure 2.
Figure 2.
Example of mediation with exposure A, mediator M, outcome Y, covariates C, and a mediator-outcome confounder L that is itself affected by the exposure.

Comment in

Similar articles

Cited by

References

    1. Robins JM, Greenland S. Identifiability and exchangeability for direct and indirect effects. Epidemiology. 1992;3(2):143–155. - PubMed
    1. Pearl J. Proceedings of the Seventeenth Conference on Uncertainty and Artificial Intelligence. San Francisco, CA: Morgan Kaufmann; 2001. Direct and indirect effects; pp. 411–420.
    1. Mendelsohn ME, Karas RH. The protective effects of estrogen on the cardiovascular system. N Engl J Med. 1999;340(23):1801–1811. - PubMed
    1. Bush TL, Barrett-Connor E, Cowan LD, et al. Cardiovascular mortality and noncontraceptive use of estrogen in women: results from the Lipid Research Clinics Program Follow-up Study. Circulation. 1987;75(6):1102–1109. - PubMed
    1. Rubin DB. Formal modes of statistical inference for causal effects. J Statist Plan Inf. 1990;25(3):279–292.

Publication types