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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 TianORCID iD [aut], Xiaotong JiangORCID iD [aut], Gabrielle SimoneauORCID iD [aut], Biogen MA Inc. [cph], Thomas DebrayORCID iD [ctb, cre], Stan WijnORCID 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.html ,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:

Please use the canonical formhttps://CRAN.R-project.org/package=precmedto link to this page.


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