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.
- Version0.0.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- personalized2part citation info
- Last release09/10/2020
Documentation
Team
Jared Huling
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Last 30 days
This package has been downloaded 128 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
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Last 365 days
This package has been downloaded 1,880 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 24 downloads.
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- Depends2 packages
- Imports2 packages
- Linking To2 packages