Biostatistics Seminar: Jamie Robins, Harvard University
DATE: Monday, Movember 18th, 2013
LOCATION: Valley Hall 1020
SPEAKER: Jamie Robins, Harvard University
TITLE: Counterfactuals, Causal Models, and SWIGs
ABSTRACT: I review identification and estimation of direct and indirect effects of time-varying treatments or actions. I describe the relationship between a number of modeling approaches: marginal structural models, the parametric g-formula, the iterated conditional expectation g-formula, direct effect structural nested models, and nested Markov models. I describe the strengths and weaknesses of each modeling approach and give examples of their application in medicine and public health. Finally I show how SWIGs (single world intervention graphs) can be used to effortlessly translate between the counterfactual and graphical approaches to causation.
THIS SEMINAR IS PRESENTED JOINTLY WITH THE GRADUATE GROUP IN EPIDEMIOLOGY