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Implements the methodology of Huling, Smith, and Chen (2020) <doi:10.1080/01621459.2020.1801449>, which allows for subgroup identification for semi-continuous outcomes by estimating individualized treatment rules. It uses a two-part modeling framework to handle semi-continuous data by separately modeling the positive part of the outcome and an indicator of whether each outcome is positive, but still results in a single treatment rule. High dimensional data is handled with a cooperative lasso penalty, which encourages the coefficients in the two models to have the same sign.
Version: | 0.0.1 |
Depends: | personalized, HDtweedie |
Imports: | Rcpp, foreach, methods |
LinkingTo: | Rcpp, RcppEigen |
Published: | 2020-09-10 |
DOI: | 10.32614/CRAN.package.personalized2part |
Author: | Jared Huling |
Maintainer: | Jared Huling <jaredhuling at gmail.com> |
BugReports: | https://github.com/jaredhuling/personalized2part/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/jaredhuling/personalized2part |
NeedsCompilation: | yes |
Citation: | personalized2part citation info |
Materials: | README |
CRAN checks: | personalized2part results |
Reference manual: | personalized2part.pdf |
Package source: | personalized2part_0.0.1.tar.gz |
Windows binaries: | r-devel: personalized2part_0.0.1.zip, r-release: personalized2part_0.0.1.zip, r-oldrel: personalized2part_0.0.1.zip |
macOS binaries: | r-release (arm64): personalized2part_0.0.1.tgz, r-oldrel (arm64): personalized2part_0.0.1.tgz, r-release (x86_64): personalized2part_0.0.1.tgz, r-oldrel (x86_64): personalized2part_0.0.1.tgz |
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These binaries (installable software) and packages are in development.
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