
Odds ratios for mediation analysis for a dichotomous outcome
- Author
- Tyler J VanderWeele and Stijn Vansteelandt (UGent)
- Organization
- 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.
- Keywords
- SURROGATE MARKER, MARGINAL STRUCTURAL MODELS, CAUSAL INFERENCE, PROPORTION, INTERVENTIONS, ESTROGEN, case-control studies, causal inference, decomposition, dichotomous response, epidemiologic methods, interaction, logistic regression, odds ratio
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-1234535
- MLA
- VanderWeele, Tyler J., and Stijn Vansteelandt. “Odds Ratios for Mediation Analysis for a Dichotomous Outcome.” AMERICAN JOURNAL OF EPIDEMIOLOGY, vol. 172, no. 12, 2010, pp. 1339–48, doi:10.1093/aje/kwq332.
- APA
- VanderWeele, T. J., & Vansteelandt, S. (2010). Odds ratios for mediation analysis for a dichotomous outcome. AMERICAN JOURNAL OF EPIDEMIOLOGY, 172(12), 1339–1348. https://doi.org/10.1093/aje/kwq332
- Chicago author-date
- VanderWeele, Tyler J, and Stijn Vansteelandt. 2010. “Odds Ratios for Mediation Analysis for a Dichotomous Outcome.” AMERICAN JOURNAL OF EPIDEMIOLOGY 172 (12): 1339–48. https://doi.org/10.1093/aje/kwq332.
- Chicago author-date (all authors)
- VanderWeele, Tyler J, and Stijn Vansteelandt. 2010. “Odds Ratios for Mediation Analysis for a Dichotomous Outcome.” AMERICAN JOURNAL OF EPIDEMIOLOGY 172 (12): 1339–1348. doi:10.1093/aje/kwq332.
- Vancouver
- 1.VanderWeele TJ, Vansteelandt S. Odds ratios for mediation analysis for a dichotomous outcome. AMERICAN JOURNAL OF EPIDEMIOLOGY. 2010;172(12):1339–48.
- IEEE
- [1]T. J. VanderWeele and S. Vansteelandt, “Odds ratios for mediation analysis for a dichotomous outcome,” AMERICAN JOURNAL OF EPIDEMIOLOGY, vol. 172, no. 12, pp. 1339–1348, 2010.
@article{1234535, 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.}}, author = {{VanderWeele, Tyler J and Vansteelandt, Stijn}}, issn = {{0002-9262}}, journal = {{AMERICAN JOURNAL OF EPIDEMIOLOGY}}, keywords = {{SURROGATE MARKER,MARGINAL STRUCTURAL MODELS,CAUSAL INFERENCE,PROPORTION,INTERVENTIONS,ESTROGEN,case-control studies,causal inference,decomposition,dichotomous response,epidemiologic methods,interaction,logistic regression,odds ratio}}, language = {{eng}}, number = {{12}}, pages = {{1339--1348}}, title = {{Odds ratios for mediation analysis for a dichotomous outcome}}, url = {{http://dx.doi.org/10.1093/aje/kwq332}}, volume = {{172}}, year = {{2010}}, }
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