Simulates a binormal model ROC dataset

Simulates an uncorrelated binormal model ROC factorial dataset

SimulateRocDataset(I = 1, J = 1, K1, K2, a, deltaA = 0, b, seed = NULL)

Arguments

I

Number of modalities, default 1

J

The number of readers, default 1

K1

Number of non-diseased cases

K2

Number of diseased cases

a

\(a\) parameter of binormal model

deltaA

Inter-modality increment in the \(a\) parameter, default zero

b

\(b\) parameter of the binormal model

seed

Initial seed, default is NULL, for random seed

Value

An ROC dataset

Details

See book Chapter 6 for details

References

Chakraborty DP (2017) Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples, CRC Press, Boca Raton, FL. https://www.routledge.com/Observer-Performance-Methods-for-Diagnostic-Imaging-Foundations-Modeling/Chakraborty/p/book/9781482214840

Examples

K1 <- 5;K2 <- 7;a <- 1.5;b <- 0.5
rocDataRaw <- SimulateRocDataset(K1 = K1, K2 = K2, a = a, b = b)