DfCreateCorCbmDataset {RJafroc} | R Documentation |
Create paired dataset for testing FitCorCbm
Description
The paired dataset is generated using bivariate sampling; details are in referenced publication
Usage
DfCreateCorCbmDataset(
seed = 123,
K1 = 50,
K2 = 50,
desiredNumBins = 5,
muX = 1.5,
muY = 3,
alphaX = 0.4,
alphaY = 0.7,
rhoNor = 0.3,
rhoAbn2 = 0.8
)
Arguments
seed |
The seed variable, default is 123; set to NULL for truly random seed |
K1 |
The number of non-diseased cases, default is 50 |
K2 |
The number of diseased cases, default is 50 |
desiredNumBins |
The desired number of bins; default is 5 |
muX |
The CBM |
muY |
The CBM |
alphaX |
The CBM |
alphaY |
The CBM ‘alpha’ parameter in condition Y |
rhoNor |
The correlation of non-diseased case z-samples |
rhoAbn2 |
The correlation of diseased case z-samples, when disease is visible in both conditions |
Details
The ROC data is bined to 5 bins in each condition.
Value
The return value is the desired dataset, suitable for testing FitCorCbm
.
References
Zhai X, Chakraborty DP (2017) A bivariate contaminated binormal model for robust fitting of proper ROC curves to a pair of correlated, possibly degenerate, ROC datasets. Medical Physics. 44(6):2207–2222.
Examples
## seed <- 1
## this gives unequal numbers of bins in X and Y conditions for 50/50 dataset
dataset <- DfCreateCorCbmDataset()
## this takes very long time!! used to show asymptotic convergence of ML estimates
## dataset <- DfCreateCorCbmDataset(K1 = 5000, K2 = 5000)