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.html , 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

Linking:

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