personalized2part: Two-Part Estimation of Treatment Rules for Semi-Continuous Data
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 
[aut, cre] |
| 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 |
Documentation:
| Reference manual: | personalized2part.pdf |
Downloads:
| 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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