R/tmle3
The Extensible TMLE framework
Author: Jeremy Coyle
What’s tmle3?
tmle3 is a general framework that supports the implementation of a
range of Targeted Maximum Likelihood / Minimum Loss-Based Estimation
(TMLE) parameters through exposing a unified interface. The goal is that
the tmle3 framework be as general as the mathematical framework upon
which it’s based.
For a general discussion of the framework of targeted minimum loss-based estimation and the role this methodology plays in statistical and causal inference, the canonical references are van der Laan and Rose (2011) and van der Laan and Rose (2018).
Installation
You can install the development version of tmle3 from GitHub via
devtools with
devtools::install_github("tlverse/tmle3")Getting Started
The best place to get started is the “Framework Overview” document,
which describes the individual components of the tmle3 framework. It
may be found at https://tlverse.org/tmle3/articles/framework.html.
Issues
If you encounter any bugs or have any specific feature requests, please file an issue.
License
© 2017-2019 Jeremy R. Coyle
The contents of this repository are distributed under the GPL-3 license.
See file LICENSE for details.
References
van der Laan, Mark J, and Sherri Rose. 2011. Targeted Learning: Causal Inference for Observational and Experimental Data. Springer Science & Business Media.
———. 2018. Targeted Learning in Data Science: Causal Inference for Complex Longitudinal Studies. Springer Science & Business Media.