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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 ORCID iD [aut], Xiaotong Jiang ORCID iD [aut], Gabrielle Simoneau ORCID iD [aut], Biogen MA Inc. [cph], Thomas Debray ORCID iD [ctb, cre], Stan Wijn ORCID iD [ctb], 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

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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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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