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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.0.2 |
rolling linux/jammy R-4.5 | personalized2part_0.0.2.tar.gz |
297.8 KiB |
0.0.2 |
rolling linux/noble R-4.5 | personalized2part_0.0.2.tar.gz |
302.9 KiB |
0.0.2 |
rolling source/ R- | personalized2part_0.0.2.tar.gz |
139.5 KiB |
0.0.2 |
latest linux/jammy R-4.5 | personalized2part_0.0.2.tar.gz |
297.8 KiB |
0.0.2 |
latest linux/noble R-4.5 | personalized2part_0.0.2.tar.gz |
302.9 KiB |
0.0.2 |
latest source/ R- | personalized2part_0.0.2.tar.gz |
139.5 KiB |
0.0.2 |
2026-04-26 source/ R- | personalized2part_0.0.2.tar.gz |
139.5 KiB |
0.0.2 |
2026-04-23 source/ R- | personalized2part_0.0.2.tar.gz |
139.5 KiB |
0.0.2 |
2026-04-09 windows/windows R-4.5 | personalized2part_0.0.2.zip |
621.7 KiB |
0.0.1 |
2025-04-20 source/ R- | personalized2part_0.0.1.tar.gz |
136.3 KiB |