roc_table: Receiver Operating Characteristic

In DavideMassidda/testing: Psychometric Testing

Receiver Operating Characteristic

Description

Calculate the sensibility and the specificity of a psychometric test for candidate cutoffs. and plot a ROC curve.

Usage

roc_table(test, gold.std, cutoff = sort(unique(test)))
## S3 method for class 'ROC'
## S3 method for class 'ROC'
plot(x, labels = TRUE, ...)

Arguments

test	Numeric vector reporting the score obtained of a test for a group of persons.
gold.std	Dichotomous vector reporting the classification performed by another test, considered as gold standard. The first value identifies negative people, the second value positive people.
cutoff	Numeric vector containing the thresholds at which to calculate the sensibility and the specificity of the test. For each threshold, people reporting a test value equal or greater of the threshold value are considered as positive. As default, all the values contained into the vector test are checked as candidate cutoffs.
x	An object of class "ROC".
labels	Logical. If true, plot the labels identifying each cutoff value.
...	Further arguments for the function plot.

Author(s)

Davide Massidda <[e-mail]>

Examples

x <- c(3,4,4,0,3,1,2,3,2,2,2,2,3,4,5,1,1,4,2,3,4,2,2,1,5,2,3,5,2,5,1,5,4,3,1)
g <- c(0,0,1,0,0,0,0,1,0,0,0,0,1,1,1,0,0,1,1,1,1,0,0,0,1,0,0,1,0,1,0,1,1,1,0)
(tab <- roc_table(x, g))
plot(tab)

DavideMassidda/testing documentation built on Oct. 12, 2023, 4:32 p.m.