ROCnReg: An R Package for Receiver Operating Characteristic Curve Inference With and Without Covariates

R J. Pub Date : 2021-01-01 DOI:10.32614/rj-2021-066
M. Rodríguez-Álvarez, Vanda Inácio
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引用次数: 8

Abstract

This paper introduces the package ROCnReg that allows estimating the pooled ROC curve, the covariate-specific ROC curve, and the covariate-adjusted ROC curve by different methods, both from (semi) parametric and nonparametric perspectives and within Bayesian and frequentist paradigms. From the estimated ROC curve (pooled, covariate-specific, or covariate-adjusted), several summary measures of discriminatory accuracy, such as the (partial) area under the ROC curve and the Youden index, can be obtained. The package also provides functions to obtain ROC-based optimal threshold values using several criteria, namely, the Youden index criterion and the criterion that sets a target value for the false positive fraction. For the Bayesian methods, we provide tools for assessing model fit via posterior predictive checks, while the model choice can be carried out via several information criteria. Numerical and graphical outputs are provided for all methods. This is the only package implementing Bayesian procedures for ROC curves.
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一个有协变量和无协变量的接收机工作特性曲线推断的R包
本文介绍了ROCnReg包,它允许从(半)参数和非参数的角度以及在贝叶斯和频率范式内,通过不同的方法估计合并的ROC曲线,协变量特定的ROC曲线和协变量调整的ROC曲线。从估计的ROC曲线(合并、协变量特异性或协变量调整)中,可以获得几种区分准确度的汇总度量,例如ROC曲线下的(部分)面积和约登指数。该包还提供了使用几个标准获得基于roc的最优阈值的函数,即约登指数准则和为假阳性分数设置目标值的准则。对于贝叶斯方法,我们提供了通过后验预测检查评估模型拟合的工具,而模型选择可以通过几个信息标准进行。所有方法都提供了数值和图形输出。这是唯一的包实现贝叶斯程序的ROC曲线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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