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 <sthollow@ncsu.edu>
LicenseGPL-2
Version4.9
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("DynTxRegime")

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DynTxRegime documentation built on Nov. 10, 2020, 1:08 a.m.