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ROCnReg (version 1.0-8)

ROC Curve Inference with and without Covariates

Description

Estimates the pooled (unadjusted) Receiver Operating Characteristic (ROC) curve, the covariate-adjusted ROC (AROC) curve, and the covariate-specific/conditional ROC (cROC) curve by different methods, both Bayesian and frequentist. Also, it provides functions to obtain ROC-based optimal cutpoints utilizing several criteria. Based on Erkanli, A. et al. (2006) ; Faraggi, D. (2003) ; Gu, J. et al. (2008) ; Inacio de Carvalho, V. et al. (2013) ; Inacio de Carvalho, V., and Rodriguez-Alvarez, M.X. (2018) ; Janes, H., and Pepe, M.S. (2009) ; Pepe, M.S. (1998) ; Rodriguez-Alvarez, M.X. et al. (2011a) ; Rodriguez-Alvarez, M.X. et al. (2011a) . Please see Rodriguez-Alvarez, M.X. and Inacio, V. (20208) for more details.

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Version

Install

install.packages('ROCnReg')

Monthly Downloads

607

Version

1.0-8

License

GPL

Maintainer

Maria Xose Rodriguez-Alvarez mxrodriguez@uvigo.es

Last Published

March 10th, 2023

Functions in ROCnReg (1.0-8)

AROC.bnp

Nonparametric Bayesian inference of the covariate-adjusted ROC curve (AROC).
compute.threshold.cROC

Covariate-specific ROC based threshold values.
cROC.sp

Parametric and semiparametric frequentist inference of the covariate-specific ROC curve (cROC).
cROCData

Selects an adequate set of points from a data set for obtaining predictions.
AROC.sp

Semiparametric frequentist inference for the covariate-adjusted ROC curve (AROC).
ROCnReg-package

tools:::Rd_package_title("ROCnReg")
cROC.kernel

Nonparametric kernel-based estimation of the covariate-specific ROC curve (cROC).
AROC.kernel

Nonparametric kernel-based estimation of the covariate-adjusted ROC curve (AROC).
cROC.bnp

Nonparametric Bayesian inference for the covariate-specific ROC curve (cROC).
compute.threshold.AROC

AROC based threshold values.
plot.cROC

Default cROC plotting
endosyn

Simulated endocrine data.
plot.AROC

Default AROC plotting
densitycontrol.aroc

Conditional density estimates of test outcomes in the healthy population
plot.pooledROC

Default pooledROC plotting
pooledROC.BB

Bayesian bootstrap estimation of the pooled ROC curve.
pauccontrol

Partial area under the covariate-adjusted/covariate-specific/pooled ROC curve
mcmccontrol

Markov chain Monte Carlo (MCMC) parameters
densitycontrol

(Conditional) density estimates of test outcomes
compute.threshold.pooledROC

Pooled ROC based threshold values.
print.cROC

Print method for cROC objects
print.AROC

Print method for AROC objects
pooledROC.kernel

Kernel-based estimation of the pooled ROC curve.
pooledROC.dpm

Nonparametric Bayesian inference of the pooled ROC curve
print.pooledROC

Print method for pooledROC objects
priorcontrol.bnp

Prior information for the AROC.bnp and cROC.bnp
psa

Prostate specific antigen (PSA) biomarker study.
pooledROC.emp

Empirical estimation of the pooled ROC curve.
priorcontrol.dpm

Prior information for the pooledROC.dpm
summary.pooledROC

Summary method for pooledROC objects
predictive.checks

Posterior predictive checks.
summary.AROC

Summary method for AROC objects
summary.cROC

Summary method for cROC objects