Question

What are the similarities and the differences between the Marginal structural model and the structural nested means model?

Answer 1

Marginal structural models are a multi-step estimation procedure designed to control for the effect of confounding variables that change over time, and are affected by previous treatment.

Structural nested models (SNMs) were designed
in part to deal with confounding by variables affected by treatment.

marginal structural models estimate the outcome of interest taking into account these weights. Marginal structural models are a powerful method for confounding control in longitudinal study designs that collect time-varying information on exposure, outcome and other covariates.

Structural nested mean models are a useful tool when estimating the effect of time-varying treatments, a challenge made more difficult by the presence of treatment-dependent confounders. We consider the situation where data are measured on, and a treatment assigned to, subjects at a number of distinct time points (or stages). We wish to identify the effect of treatment at each stage on a final (continuous) outcome, when all time-varying confounders are correctly measured, with each treatment’s effect characterized by a structural nested mean model. For example, consider a study of the effect of activity level (the treatment) on blood pressure (the outcome), with data collected by repeated questionnaires over time.