tlverse/tmle3mopttx: Targeted Maximum Likelihood Estimation of the Mean under Optimal Individualized Treatment

This package estimates the optimal individualized treatment rule for the categorical treatment using Super Learner (sl3). In order to avoid nested cross-validation, it uses split-specific estimates of Q and g to estimate the rule as described by Coyle et al. In addition, it provides the Targeted Maximum Likelihood estimates of the mean performance using CV-TMLE under such estimated rules. This is an adapter package for use with the tmle3 framework and the tlverse software ecosystem for Targeted Learning.

Getting started

Package details

Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
tlverse/tmle3mopttx documentation built on Feb. 29, 2020, 1:09 p.m.