AUC: Area under the curve (AUC)

In mada: Meta-Analysis of Diagnostic Accuracy

Area under the curve (AUC)

Description

Calculates the area under the curve given a function or a fitted model.

Usage

## Default S3 method:
AUC(x, fpr = 1:99/100, ...)
## S3 method for class 'phm'
AUC(x, level = 0.95, ...)
## S3 method for class 'reitsma'
AUC(x, fpr = 1:99/100, sroc.type = "ruttergatsonis", ...)

Arguments

x	a function with range and domain in ROC space (default method) or an object of class phm or reitsma.
fpr	numeric vector, points on which the (S)ROC curve is evaluated
level	numeric, confidence level for the calculations of confidence intervals.
sroc.type	character, which SROC curve should be used to calculate the AUC? Besides the default ruttergatsonis the option naive is available.
...	further arguments, currently not used.

Details

The area under the curve is calculated using the trapezoidal rule. The argument fpr is the grid on which the (S)ROC curve is evaluated. In many cases the default grid will contain points on which the SROC curve can only be calculated by extrapolation; however if only a subinterval is specified a partial AUC is calculated and the AUC value might differ substantially.

For phm objects the AUC and its confidence interval is calculated analytically, for reitsma objects a call to the default method is invoked.

Value

An object of the class AUC which is really a list with component AUC and an optional component ci, which is currently only available from the AUC method for phm ojects.

Author(s)

Philipp Doebler <[e-mail]>

Examples

data(AuditC)
AUC(phm(AuditC))

mada documentation built on Sept. 9, 2022, 3:01 p.m.