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personalized: Estimation and Validation Methods for Subgroup Identification and Personalized Medicine

Provides functions for fitting and validation of models for subgroup identification and personalized medicine / precision medicine under the general subgroup identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>. This package is intended for use for both randomized controlled trials and observational studies and is described in detail in Huling and Yu (2021) <doi:10.18637/jss.v098.i05>.

Version: 0.2.7
Depends: glmnet (≥ 2.0-13), mgcv, ggplot2, plotly
Imports: survival, methods, kernlab, foreach, xgboost
Suggests: knitr, rmarkdown, testthat, nnet
Published: 2022-06-27
Author: Jared Huling ORCID iD [aut, cre], Aaron Potvien [ctb], Alexandros Karatzoglou [cph], Alex Smola [cph]
Maintainer: Jared Huling <jaredhuling at gmail.com>
BugReports: https://github.com/jaredhuling/personalized/issues
License: GPL-2
URL: https://jaredhuling.org/personalized/, https://arxiv.org/abs/1809.07905
NeedsCompilation: no
Citation: personalized citation info
Materials: README NEWS
In views: CausalInference
CRAN checks: personalized results

Documentation:

Reference manual: personalized.pdf
Vignettes: Utilities for Improving Estimation Efficiency via Augmentation and for Propensity Score Estimation
Estimation of Flexible ITRs with xgboost
Multi-category Treatments with 'personalized'
Usage of the Personalized Package

Downloads:

Package source: personalized_0.2.7.tar.gz
Windows binaries: r-devel: personalized_0.2.7.zip, r-release: personalized_0.2.7.zip, r-oldrel: personalized_0.2.7.zip
macOS binaries: r-release (arm64): personalized_0.2.7.tgz, r-oldrel (arm64): personalized_0.2.7.tgz, r-release (x86_64): personalized_0.2.7.tgz, r-oldrel (x86_64): personalized_0.2.7.tgz
Old sources: personalized archive

Reverse dependencies:

Reverse depends: personalized2part

Linking:

Please use the canonical form https://CRAN.R-project.org/package=personalized to link to this page.

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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