trinROC (version 0.6)

emp.vus: Empirical VUS calculation

Description

This function computes the empirical Volume Under the Surface (VUS) of three-class ROC data.

Usage

emp.vus(x, y, z, dat = NULL, old.version = TRUE)

Value

It returns the numeric VUS of the data.

Arguments

x, y, z

Numeric vectors contaning the measurements from the healthy, intermediate and diseased class.

dat

A data frame of the following structure: The first column represents a factor with three levels, containing the true class membership of each measurement. The levels are ordered according to the convention of higher values for more severe disease status. The second column contains all measurements obtained from Classifier.

old.version

A logical to switch computation method to the old version, which is up to 50% faster in computation (at N=50).

Details

This function computes the empirical VUS of three-class ROC data using the expand.grid function. It has been shown to be faster than computation using the merge function (VUS.merge()) or direct geometrical imlementation. The measurements can be input as seperate vectors x, y, z or as a data frame dat.

References

Scurfield, B. K. (1996). Multiple-event forced-choice tasks in the theory of signal detectability. Journal of Mathematical Psychology 40.3, 253–269.

Nakas CT and Yiannoutsos CT (2004) Ordered multiple-class roc analysis with continuous measurements. Statistics in Medicine 23(22): 3437–3449.

Examples

data(krebs)
x1 <- with(krebs, cancer[trueClass=="healthy", 4])
y1 <- with(krebs, cancer[trueClass=="intermediate", 4])
z1 <- with(krebs, cancer[trueClass=="diseased", 4])

emp.vus(x1, y1, z1)
# Alternatively:
emp.vus(dat = krebs[,c(1,4)])