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rocbc
View on CRAN: Click
here
Download and install rocbc package within the R console
Install from CRAN:
install.packages("rocbc")
Install from Github:
library("remotes")
install_github("cran/rocbc")
Install by package version:
library("remotes")
install_version("rocbc", "3.1.0")
Attach the package and use:
library("rocbc")
Maintained by
Benjamin Brewer
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-20
Latest Update: 2023-04-04
Description:
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.
How to cite:
Benjamin Brewer (2022). rocbc: Statistical Inference for Box-Cox Based Receiver Operating Characteristic Curves. R package version 3.1.0, https://cran.r-project.org/web/packages/rocbc
Previous versions and publish date:
Other packages that cited rocbc R package
View rocbc citation profile
Other R packages that rocbc depends,
imports, suggests or enhances
Functions, R codes and Examples using
the rocbc R package
Some associated functions: checkboxcox . checkboxcox2 . comparebcAUC . comparebcJ . comparebcSens . comparebcSpec . rocboxcox . rocboxcoxCI .
Some associated R codes: checkboxcox.R . checkboxcox2.R . comparebcAUC.R . comparebcJ.R . comparebcSens.R . comparebcSpec.R . rocboxcox.R . rocboxcoxCI.R . Full rocbc package functions and examples
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