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  [aut]
(<https://orcid.org/0000-0002-5893-0169>),
Xiaotong Jiang
[aut] (<https://orcid.org/0000-0003-3698-4526>),
Gabrielle Simoneau
[aut]
(<https://orcid.org/0000-0001-9310-6274>),
Biogen MA Inc. [cph],
Thomas Debray
[ctb, cre] (<https://orcid.org/0000-0002-1790-2719>),
Stan Wijn [ctb]
(<https://orcid.org/0000-0003-3782-6677>),
Joana Caldas [ctb] |
| 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 |