Department of Statistics Seminar
North Carolina State University

presents

Dr. James M. Robins

Harvard University

"Marginal Structural Models and Inverse-probability-of-treatment weighted Estimators"

ABSTRACT

In observational studies, with exposures or treatments that vary over time, standard approaches for adjustment of confounding are biased when there exist time-dependent confounders that are also intermediate variables. This talk introduces marginal structural models (MSMs), a new class of causal models that allow for improved adjustment of confounding in those situations. The parameters of a MSM can be consistently estimated using a new class of estimators: the inverse-probability-of-treatment weighted estimators. The relationship of MSMs to propensity score methods is considered. I also discuss how to conduct a sensitiivity analysis using MSMs that alows for confounding by unmeasured confounders.

Friday, February 11, 2000

3:35 - 4:35 pm

206 Cox Hall

Refreshments will be served on the second floor of Dabney Hall (left of Room 222) at 3:00 pm.