Marginal structural models are a class of

statistical model A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of Sample (statistics), sample data (and similar data from a larger Statistical population, population). A statistical model repres ...

s used for

causal inference Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference ana ...

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 evidenc ...

. 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 in

AIDS Human immunodeficiency virus infection and acquired immunodeficiency syndrome (HIV/AIDS) is a spectrum of conditions caused by infection with the human immunodeficiency virus (HIV), a retrovirus. Following initial infection an individual m ...

-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 or

bilirubin Bilirubin (BR) (Latin for "red bile") is a red-orange compound that occurs in the normal catabolic pathway that breaks down heme in vertebrates. This catabolism is a necessary process in the body's clearance of waste products that arise from the ...

. 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 th ...

, Babette Brumback, and

Miguel Hernán Miguel Hernán is a Spanish–American epidemiologist. He is the Director of the CAUSALab, Kolokotrones Professor of Biostatistics and Epidemiology at the Harvard T.H. Chan School of Public Health, and Member of the Faculty at the Harvard–MIT Pro ...

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