Marginal structural models and causal inference in epidemiology

Robins, JM; Hernán, MA; Brumback, B

HERO ID

11319809

Reference Type

Journal Article

Subtype

Editorial

Year

2000

Language

English

PMID

10955408

HERO ID 11319809
Material Type Editorial
In Press No
Year 2000
Title Marginal structural models and causal inference in epidemiology
Authors Robins, JM; Hernán, MA; Brumback, B
Journal Epidemiology
Volume 11
Issue 5
Page Numbers 550-560
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.
Doi 10.1097/00001648-200009000-00011
Pmid 10955408
Wosid WOS:000088854500011
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English
Keyword causality; counterfactuals; epidemiologic methods; longitudinal data; structural models; confounding; intermediate variables