CSS Seminar - Tyler Vander Weele

Tyler Vander Weele, PhD, Associate Professor of Epidemiology, Harvard School of Public Health
Marginal Structural Models for Sufficient Cause Interactions
Sufficient cause interactions concern cases in which a particular causal mechanism for some outcome will operate only if two or more specific causes are present. Empirical conditions have been derived to test for sufficient cause interactions. However, when regression outcome models are used to control for confounding variables in tests for sufficient cause interactions, the outcome models impose restrictions on the relationship between the confounding variables and certain unidentified background causes within the sufficient cause framework; often these assumptions are implausible. By using marginal structural models, rather than outcome regression models, to test for sufficient cause interactions, assumptions are instead made on the relationship between the causes of interest and the confounding variables; these assumptions will often be more plausible. The use of marginal structural models also allows for testing for sufficient cause interactions in the presence of time-dependent confounding. Such time-dependent confounding may arise in cases in which a genetic factor of interest affects both an environmental factor of interest and the outcome. It is furthermore shown that marginal structural models can be used not only to test for sufficient cause interactions but to give lower bounds on the prevalence of such sufficient cause interactions. The methods are illustrated with an application to sufficient cause interactions between the effects of well-arsenic exposure and smoking on the development of skin lesions using data from a study in Bangladesh.
Location:121 S. Main Street, Room 245