Marginal structural models and causal inference in epidemiology (2000)
| Venue: | Epidemiology |
| Citations: | 105 - 2 self |
BibTeX
@ARTICLE{Robins00marginalstructural,
author = {James M. Robins and Miguel Ángel Hernán and Babette Brumback},
title = {Marginal structural models and causal inference in epidemiology},
journal = {Epidemiology},
year = {2000},
volume = {11},
pages = {550--560}
}
Share
 |
 |
 |
 |
||
OpenURL
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 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 weighted estimators. (Epidemiology 2000;11:550–560)
