G-formula (sometimes known as G-computation) is an approach for estimating the causal effects of treatments or exposures which can vary over time and which are subject to time-varying confounding. It is one of the so called G-methods developed by Jamie Robins and co-workers. For a nice overview of these, I recommend this open access paper by Naimi et al 2017, and for more details, the What If book by Hernán and Robins. In this post, I’ll describe some recent work with Camila Olarte Parra and Rhian Daniel in which we have explored the use of multiple imputation methods and software as a route to implementing G-formula estimators.