DynTxRegime: Methods for Estimating Optimal Dynamic Treatment Regimes

Methods to estimate dynamic treatment regimes using Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods based on Augmented Inverse Probability Weighted Estimators and Inverse Probability Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.

Getting started

Package details

AuthorS. T. Holloway, E. B. Laber, K. A. Linn, B. Zhang, M. Davidian, and A. A. Tsiatis
MaintainerShannon T. Holloway <shannon.t.holloway@gmail.com>
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the DynTxRegime package in your browser

Any scripts or data that you put into this service are public.

DynTxRegime documentation built on Nov. 25, 2023, 1:09 a.m.