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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.
Getting started
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Package details |
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| Author | Jared Huling [aut, cre] (<https://orcid.org/0000-0003-0670-4845>) |
| Maintainer | Jared Huling <jaredhuling@gmail.com> |
| License | GPL (>= 2) |
| Version | 0.0.1 |
| URL | https://github.com/jaredhuling/personalized2part |
| Package repository | View on CRAN |
| Installation |
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