calculate_roc: Calculate the Empirical ROC curve

In plotROC: Generate Useful ROC Curve Charts for Print and Interactive Use

Calculate the Empirical ROC curve

Description

Deprecated, use geom_roc instead

Usage

calculate_roc(M, D, ci = FALSE, alpha = 0.05)

Arguments

M	continuous marker values or predictions of class labels
D	class labels, must be coded as 0 and 1. If not numeric with 0/1, then plotROC assumes the first level in sort order is healthy status, with a warning.
ci	Logical, if true, will calculate exact joint confidence regions for the TPF and FPF
alpha	Confidence level, ignored if ci = FALSE

Details

Confidence intervals for TPF and FPF are calculated using the exact method of Clopper and Pearson (1934) each at the level 1 - sqrt(1 - alpha). Based on result 2.4 from Pepe (2003), the cross-product of these intervals yields a 1 - alpha

Value

A dataframe containing cutoffs, estimated true and false positive fractions, and confidence intervals if ci = TRUE.

plotROC documentation built on Oct. 6, 2023, 5:10 p.m.