precmed: Precision Medicine
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 |
Documentation:
| Reference manual: | precmed.pdf |
Downloads:
| 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 |
Linking:
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