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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.

Version: 4.15
Depends: methods, modelObj, stats
Imports: kernlab, rgenoud, dfoptim
Suggests: MASS, rpart, nnet
Published: 2023-11-24
DOI: 10.32614/CRAN.package.DynTxRegime
Author: S. T. Holloway, E. B. Laber, K. A. Linn, B. Zhang, M. Davidian, and A. A. Tsiatis
Maintainer: Shannon T. Holloway <shannon.t.holloway at gmail.com>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
In views: CausalInference
CRAN checks: DynTxRegime results

Documentation:

Reference manual: DynTxRegime.pdf

Downloads:

Package source: DynTxRegime_4.15.tar.gz
Windows binaries: r-devel: DynTxRegime_4.15.zip, r-release: DynTxRegime_4.15.zip, r-oldrel: DynTxRegime_4.15.zip
macOS binaries: r-release (arm64): DynTxRegime_4.15.tgz, r-oldrel (arm64): DynTxRegime_4.15.tgz, r-release (x86_64): DynTxRegime_4.15.tgz, r-oldrel (x86_64): DynTxRegime_4.15.tgz
Old sources: DynTxRegime archive

Reverse dependencies:

Reverse imports: DevTreatRules, polle

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DynTxRegime to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.