Package: DevTreatRules
Type: Package
Title: Develop Treatment Rules with Observational Data
Version: 1.1.0
Authors@R: c(person("Jeremy", "Roth", email = "jhroth@uw.edu", role=c("cre", "aut")),
                         person("Noah", "Simon", email = "nrsimon@uw.edu", role="aut"))
Description: 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.
Depends: R (>= 3.2.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
VignetteBuilder: knitr
Imports: glmnet, DynTxRegime, modelObj
Suggests: dplyr, knitr, rmarkdown
NeedsCompilation: no
Packaged: 2020-03-20 15:22:59 UTC; jeremy
Author: Jeremy Roth [cre, aut],
  Noah Simon [aut]
Maintainer: Jeremy Roth <jhroth@uw.edu>
Repository: CRAN
Date/Publication: 2020-03-20 17:40:05 UTC
Built: R 4.6.0; ; 2026-04-26 06:56:10 UTC; unix
