# Replications for introduction to g-methods: marginal structural models (part 2)

** Published:**

This tutorial series aims to replicate g-methods explained in this paper by Naimi, A. I., Cole, S. R., and Kennedy, E. H (2017)^{1} using **R**. Originally, the paper used SAS to demonstrate g-methods.

In this tutorial, we will focus on replicating the results using **marginal structural models** to estimate the average causal effects of always taking treatment and compared to never-taking treatment. From our knowledge of the data-generating process, we know this average causal effect to be \(50\). In our tutorial, we will pay more attention to computation rather than proofs to perform replciations.

**Reminder: Our Settings**

Naimi, A. I., Cole, S. R., & Kennedy, E. H. (2017). An introduction to g methods. International journal of epidemiology, 46(2), 756-762. ↩