Marginal structural models are a class of
statistical models used for
causal inference in
epidemiology
Epidemiology is the study and analysis of the distribution (who, when, and where), patterns and determinants of health and disease conditions in a defined population.
It is a cornerstone of public health, and shapes policy decisions and evide ...
. Such models handle the issue of time-dependent confounding in evaluation of the efficacy of interventions by
inverse probability weighting Inverse probability weighting is a statistical technique for calculating statistics standardized to a pseudo-population different from that in which the data was collected. Study designs with a disparate sampling population and population of target ...
for receipt of treatment, they allow us to estimate the average causal effects. For instance, in the study of the effect of
zidovudine
Zidovudine (ZDV), also known as azidothymidine (AZT), is an antiretroviral medication used to prevent and treat HIV/AIDS. It is generally recommended for use in combination with other antiretrovirals. It may be used to prevent mother-to-child ...
in
AIDS-related mortality,
CD4 lymphocyte is used both for treatment indication, is influenced by treatment, and affects survival. Time-dependent confounders are typically highly prognostic of health outcomes and applied in dosing or indication for certain therapies, such as body weight or lab values such as
alanine aminotransferase
Alanine transaminase (ALT) is a transaminase enzyme (). It is also called alanine aminotransferase (ALT or ALAT) and was formerly called serum glutamate-pyruvate transaminase or serum glutamic-pyruvic transaminase (SGPT) and was first character ...
or
bilirubin.
The first marginal structural models were introduced in 2000. The works of
James Robins
James M. Robins is an epidemiologist and biostatistician best known for advancing methods for drawing causal inferences from complex observational studies and randomized trials, particularly those in which the treatment varies with time. He is ...
,
Babette Brumback, and
Miguel Hernán provided an intuitive theory and an easy-to-implement software which made them popular for the analysis of longitudinal data.
References
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External links
Statistical models
Epidemiology
Causal inference