gesttools: General Purpose G-Estimation in R

Abstract

Abstract:In this paper we present gesttools, a series of general purpose, user friendly functions with which to perform g-estimation of structural nested mean models (SNMMs) for time-varying exposures and outcomes in R. The package implements the g-estimation methods found in Vansteelandt and Sjolander (2016) and Dukes and Vansteelandt (2018), and is capable of analysing both end of study and time-varying outcome data that are either binary or continuous, or exposure variables that are either binary, continuous, or categorical. It also allows for the fitting of SNMMs with time-varying causal effects, effect modification by other variables, or both, as well as support for censored data using inverse weighting. We outline the theory underpinning these methods, as well as describing the SNMMs that can be fitted by the software. The package is demonstrated using simulated, and real-world inspired datasets.