AUC.default {sensR}R Documentation

AUC computation

Description

This is the default AUC function for scalar d-primes, which will compute Area Under the ROC curve (ROC is an acronym for receiver operating characteristic).

Usage

## Default S3 method:
AUC(d, scale = 1, se.d, CI.alpha = 0.05, ...)
## S3 method for class 'discrim':
AUC(d, CI.alpha = 0.05, ...)

Arguments

d a unit lenght vector with the value of d-prime for which AUC is to be computed or a discrim object from the fitting of a A-not A test with AnotA
scale a unit length vector giving the ratio of scale (ie. standard deviation) of the latent distribution for the no-class items relative to that of the yes-class items
se.d standard error of d (d-prime). If provided, the function will compute confidence limits of value of AUC—cf. in section value.
CI.alpha the type I level of the confidence interval of AUC
... additional arguments passed integrate

Details

The function calls integrate to obtain the area under the ROC curve implied by d and scale.

Confidence limits are based on a normal approximation of d and not of AUC. The limits are computed, if an estimate of the standard error of d is provided. Note that the limits does not take the uncertainty in estimating the scale nor that of estimating the standard error of d into account.

Value

A list with components. If se.d is supplied to the default method or if a discrim object is supplied, the object contains the latter three additional elements.

value the estimated value of AUC
res.int the result from the call to integrate
lower the lower confidence limit
upper the upper confidence limit
CI.alpha echoes the provided CI.alpha

Author(s)

Rune Haubo B Christensen

Examples

(odor <- matrix(c(112, 112, 72, 53, 22, 4, 7, 38, 50, 117, 101, 62), 2,
               byrow = TRUE))
(d.primes <- SDT(odor)[,3])
for(i in 1:5) print(AUC(d.primes[i]))
## Provide standard error of d-prime and compute CI:
fm1 <- AnotA(8, 25, 1, 25)
AUC(fm1$coef, , fm1$se)
AUC(fm1)

[Package sensR version 1.1.0 Index]