Edited by faculty of the Harvard School of Public Health
Ed. by Tchetgen Tchetgen, Eric J / VanderWeele, Tyler J. / Daniel, Rhian
The paper considers the properties of and relations between confounding and effect modification from the perspective of causal inference and with a distinction drawn as to how each of these two epidemiologic concepts can be defined both with respect to a distribution of potential outcomes or with respect to a specific effect measure. Both concepts are conditional on other covariates but the form this conditionality takes differs. Both concepts are also properties of the population, and both are relative to the specific exposure and to the specific outcome. For a particular population, the presence of confounding depends on how the exposure was assigned; the presence of effect modification does not. The possibility of confounding without effect modification and vice versa is discussed both with respect to distribution and measure. Discussion is given as to how confounding and effect modification relate to statistical models and to the relevance of the points made in the paper to data analysis and interpretation.
Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.