A doubly robust precision medicine approach to fit, cross-validate and visualize prediction models for the conditional average treatment effect (CATE). It implements doubly robust estimation and semiparametric modeling approach of treatment-covariate interactions as proposed by Yadlowsky et al. (2020) <doi:10.1080/01621459.2020.1772080>.
| Version: | 1.1.0 | 
| Depends: | R (≥ 3.5.0) | 
| Imports: | dplyr, gbm, gam, ggplot2, glmnet, graphics, MASS, mgcv, rlang, stringr, tidyr, survival, randomForestSRC | 
| Published: | 2024-10-05 | 
| DOI: | 10.32614/CRAN.package.precmed | 
| Author: | Lu Tian  | 
| Maintainer: | Thomas Debray <tdebray at fromdatatowisdom.com> | 
| BugReports: | https://github.com/smartdata-analysis-and-statistics/precmed/issues | 
| License: | Apache License (== 2.0) | 
| URL: | https://github.com/smartdata-analysis-and-statistics/precmed, https://smartdata-analysis-and-statistics.github.io/precmed/ | 
| NeedsCompilation: | no | 
| Materials: | README, NEWS | 
| CRAN checks: | precmed results | 
| Reference manual: | precmed.html , precmed.pdf | 
| Package source: | precmed_1.1.0.tar.gz | 
| Windows binaries: | r-devel: precmed_1.1.0.zip, r-release: precmed_1.1.0.zip, r-oldrel: precmed_1.1.0.zip | 
| macOS binaries: | r-release (arm64): precmed_1.1.0.tgz, r-oldrel (arm64): precmed_1.1.0.tgz, r-release (x86_64): precmed_1.1.0.tgz, r-oldrel (x86_64): precmed_1.1.0.tgz | 
| Old sources: | precmed archive | 
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