cgAUC (version 1.2.1)

cgAUC-package: Calculate AUC when gold standard is continuous with large variables.

Description

In this package, the cgAUC is used to calculate the AUC-type measure raised in Obuchowski(2006) when gold standard is continuous.

Details

Package:

cgAUC

Type:

Package

Version:

1.2.1

Date:

2014-08-24

License:

GPL (>=2)

References

Chang, YCI. Maximizing an ROC type measure via linear combination of markers when the gold reference is continuous. Statistics in Medicine 2012. Obuchowski NA. An ROC-type measure of diagnostic accuracy when the gold standard is continuous-scale. Statistics in Medicine 2006; 25:481--493. Obuchowski N. Estimating and comparing diagnostic tests accuracy when the gold standard is not binary. Statistics in Medicine 2005; 20:3261--3278. Friedman JH, Popescu BE. Gradient directed regularization for linear regression and classification. Technical Report, Department of Statistics, Stanford University, 2004.

Examples

# n = 100; p = 5;
# r.x = matrix(rnorm(n * p), , p) # raw data
# r.z = r.x[ ,1] + rnorm(n) # gold standard
# x = scale(r.x) # standardized of raw data
# z = scale(r.z) # standardized of gold standard
# h = n^(-1 / 2)
# t1 = cgAUC(r.x, r.z, h, delta = 1, auto = FALSE, tau = 1, scale = 1) # the delta be constant
# t1
# t2 = cgAUC(r.x, r.z, h, delta = 1, auto = TRUE, tau = 1, scale = 1) # the delta be variable
# t2