MR Dictionary

Structural Mean Models (SMMs)

A SMM is a semi-parametric estimation method designed for analysing data from randomized control trials (RCTs) where there is incomplete compliance. Additive and multiplicative SMMs were originally developed for instrumental variable (IV) estimation of the effects of time-varying exposures on outcomes of interest using counterfactuals to characterize the consequences of between-subject heterogeneity in the treatment effect.

SMMs can be applied to MR, such that the first stage regression model does not need to be specified. In the context of MR (and, indeed other IV approaches), IV analyses estimate the average causal effect of an exposure on an outcome and these estimators can be represented by parameters of particular structural mean models. In particular, various SMMs (e.g., additive or multiplicative SMMs) can be used within one-sample MR settings to estimate the causal effect of an exposure on an outcome. For this method to provide a valid causal estimate of the exposure on the outcome, genetic variants must satisfy the MR assumptions. However, there is no need to specify the first stage association (e.g., between the genetic variant and exposure) model. This method can also be extended to handle binary outcomes. 


Other terms in 'One-sample MR methods':