Learn R Programming

modelROC (version 1.0)

Model Based ROC Analysis

Description

The ROC curve method is one of the most important and commonly used methods for model accuracy assessment, which is one of the most important elements of model evaluation. The 'modelROC' package is a model-based ROC assessment tool, which directly works for ROC analysis of regression results for logistic regression of binary variables, including the glm() and lrm() commands, and COX regression for survival analysis, including the cph() and coxph() commands. The most important feature of 'modelROC' is that both the model and the independent variables can be analysed simultaneously, and for survival analysis multiple time points and area under the curve analysis are supported. Still, flexible visualisation is possible with the 'ggplot2' package. Reference are Kelly H. Zou (1998) and P J Heagerty (2000) .

Copy Link

Version

Install

install.packages('modelROC')

Monthly Downloads

16

Version

1.0

License

GPL-3

Maintainer

Jing Zhang

Last Published

June 25th, 2021

Functions in modelROC (1.0)

ggplot

Plot for ROC curve
auc

auc for model
roc

roc for model
unique

Extract data from roc() function