emp.vus | R Documentation |
This function computes the empirical Volume Under the Surface (VUS) of three-class ROC data.
emp.vus(x, y, z, dat = NULL, old.version = TRUE)
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). |
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
.
It returns the numeric VUS
of the data.
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.
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)])
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