Two-Part Estimation of Treatment Rules for Semi-Continuous Data

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.


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("personalized2part")

0.0.1 by Jared Huling, 2 months ago


https://github.com/jaredhuling/personalized2part


Report a bug at https://github.com/jaredhuling/personalized2part/issues


Browse source code at https://github.com/cran/personalized2part


Authors: Jared Huling [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, foreach, methods

Depends on personalized, HDtweedie

Linking to Rcpp, RcppEigen


See at CRAN