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DevTreatRules: Develop Treatment Rules with Observational Data

Develop and evaluate treatment rules based on: (1) the standard indirect approach of split-regression, which fits regressions separately in both treatment groups and assigns an individual to the treatment option under which predicted outcome is more desirable; (2) the direct approach of outcome-weighted-learning proposed by Yingqi Zhao, Donglin Zeng, A. John Rush, and Michael Kosorok (2012) <doi:10.1080/01621459.2012.695674>; (3) the direct approach, which we refer to as direct-interactions, proposed by Shuai Chen, Lu Tian, Tianxi Cai, and Menggang Yu (2017) <doi:10.1111/biom.12676>. Please see the vignette for a walk-through of how to start with an observational dataset whose design is understood scientifically and end up with a treatment rule that is trustworthy statistically, along with an estimation of rule benefit in an independent sample.

Version: 1.1.0
Depends: R (≥ 3.2.0)
Imports: glmnet, DynTxRegime, modelObj
Suggests: dplyr, knitr, rmarkdown
Published: 2020-03-20
DOI: 10.32614/CRAN.package.DevTreatRules
Author: Jeremy Roth [cre, aut], Noah Simon [aut]
Maintainer: Jeremy Roth <jhroth at uw.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: DevTreatRules results

Documentation:

Reference manual: DevTreatRules.pdf
Vignettes: DevTreatRules

Downloads:

Package source: DevTreatRules_1.1.0.tar.gz
Windows binaries: r-devel: DevTreatRules_1.1.0.zip, r-release: DevTreatRules_1.1.0.zip, r-oldrel: DevTreatRules_1.1.0.zip
macOS binaries: r-release (arm64): DevTreatRules_1.1.0.tgz, r-oldrel (arm64): DevTreatRules_1.1.0.tgz, r-release (x86_64): DevTreatRules_1.1.0.tgz, r-oldrel (x86_64): DevTreatRules_1.1.0.tgz
Old sources: DevTreatRules archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DevTreatRules 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.
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