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 affected by previous treatment. This paper introduces marginal
structural models, a new class of causal models that allow for improved adjustment of
confounding in those situations. The parameters of a marginal structural model can be
consistently estimated using a new class of estimators, the inverse-probability-of-treatment …