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.


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install.packages("DynTxRegime")

4.8 by Shannon T. Holloway, 5 days ago


Browse source code at https://github.com/cran/DynTxRegime


Authors: S. T. Holloway , E. B. Laber , K. A. Linn , B. Zhang , M. Davidian , and A. A. Tsiatis


Documentation:   PDF Manual  


GPL-2 license


Imports kernlab, rgenoud, dfoptim

Depends on methods, modelObj, stats

Suggests MASS, rpart, nnet


Imported by DevTreatRules.


See at CRAN