rocbc: Statistical Inference for Box-Cox Based Receiver Operating Characteristic Curves

Generation of Box-Cox based ROC curves and several aspects of inferences and hypothesis testing. Can be used when inferences for one biomarker (Bantis LE, Nakas CT, Reiser B. (2018) <doi:10.1002/bimj.201700107>) are of interest or when comparisons of two correlated biomarkers (Bantis LE, Nakas CT, Reiser B. (2021) <doi:10.1002/bimj.202000128>) are of interest. Provides inferences and comparisons around the AUC, the Youden index, the sensitivity at a given specificity level (and vice versa), the optimal operating point of the ROC curve (in the Youden sense), and the Youden based cutoff.

Version: 0.2.0
Imports: pracma, clinfun, splancs, mvtnorm
Suggests: knitr, markdown, matlab
Published: 2022-11-16
Author: Leonidas Bantis [aut], Benjamin Brewer [cre, ctb], Christos Nakas [ctb], Benjamin Reiser [ctb]
Maintainer: Benjamin Brewer <tennisbenj at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: rocbc results

Documentation:

Reference manual: rocbc.pdf
Vignettes: rocbc

Downloads:

Package source: rocbc_0.2.0.tar.gz
Windows binaries: r-devel: rocbc_0.2.0.zip, r-release: rocbc_0.2.0.zip, r-oldrel: rocbc_0.2.0.zip
macOS binaries: r-release (arm64): rocbc_0.2.0.tgz, r-oldrel (arm64): rocbc_0.2.0.tgz, r-release (x86_64): rocbc_0.2.0.tgz, r-oldrel (x86_64): rocbc_0.2.0.tgz
Old sources: rocbc archive

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