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personalized2part  

Two-Part Estimation of Treatment Rules for Semi-Continuous Data
View on CRAN: Click here


Download and install personalized2part package within the R console
Install from CRAN:
install.packages("personalized2part")

Install from Github:
library("remotes")
install_github("cran/personalized2part")

Install by package version:
library("remotes")
install_version("personalized2part", "0.0.1")



Attach the package and use:
library("personalized2part")
Maintained by
Jared Huling
[Scholar Profile | Author Map]
First Published: 2020-09-10
Latest Update: 2020-09-10
Description:
Implements the methodology of Huling, Smith, and Chen (2020) , 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.
How to cite:
Jared Huling (2020). personalized2part: Two-Part Estimation of Treatment Rules for Semi-Continuous Data. R package version 0.0.1, https://cran.r-project.org/web/packages/personalized2part. Accessed 01 May. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for personalized2part
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