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.

Version: 4.3
Depends: methods, modelObj, stats
Imports: kernlab, rgenoud, dfoptim
Suggests: MASS, rpart, nnet
Published: 2019-12-13
Author: S. T. Holloway, E. B. Laber, K. A. Linn, B. Zhang, M. Davidian, and A. A. Tsiatis
Maintainer: Shannon T. Holloway <sthollow at ncsu.edu>
License: GPL-2
NeedsCompilation: no
Materials: NEWS
CRAN checks: DynTxRegime results


Reference manual: DynTxRegime.pdf
Package source: DynTxRegime_4.3.tar.gz
Windows binaries: r-prerelease: DynTxRegime_4.3.zip, r-release: DynTxRegime_4.3.zip, r-oldrel: DynTxRegime_4.3.zip
macOS binaries: r-prerelease: DynTxRegime_4.3.tgz, r-release: DynTxRegime_4.3.tgz, r-oldrel: DynTxRegime_4.3.tgz
Old sources: DynTxRegime archive

Reverse dependencies:

Reverse imports: DevTreatRules


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