datasetBinned123: Binned dataset suitable for checking 'FitCorCbm'; seed = 123

In RJafroc: Artificial Intelligence Systems and Observer Performance

Binned dataset suitable for checking FitCorCbm; seed = 123

Description

A binned dataset suitable for analysis by FitCorCbm. It was generated by DfCreateCorCbmDataset by setting the seed variable to 123. Note the formatting of the data as a single treatment two reader dataset, even though the actual pairing might be different, see FitCorCbm. The dataset is intentionally large so as to demonstrate the asymptotic convergence of ML estimates, produced by FitCorCbm, to the population values. The data was generated by the following argument values to DfCreateCorCbmDataset: seed = 123, K1 = 5000, K2 = 5000, desiredNumBins = 5, muX = 1.5, muY = 3, alphaX = 0.4, alphaY = 0.7, rhoNor = 0.3, rhoAbn2 = 0.8.

Usage

datasetBinned123

Format

A list with 3 elements: $ratings, $lesions and $descriptions; $ratings contain 3 elements, $NL, $LL and $LL_IL as sub-lists; $lesions contain 3 elements, $perCase, $IDs and $weights as sub-lists; $descriptions contain 7 elements, $fileName, $type, $name, $truthTableStr, $design, $modalityID and $readerID as sub-lists;

• rating$NL, num [1, 1:2, 1:10000, 1], ratings of non-lesion localizations, NLs

• rating$LL, num [1, 1:2, 1:5000, 1], ratings of lesion localizations, LLs

• rating$LL_ILNA, this placeholder is used only for LROC data

• lesions$perCase, int [1:5000], number of lesions per diseased case

• lesions$IDs, num [1:5000, 1] , numeric labels of lesions on diseased cases

• lesions$weights, num [1:5000, 1], weights (or clinical importances) of lesions

• descriptions$fileName, chr, "datasetBinned123", base name of dataset in 'data' folder

• descriptions$type, chr "ROC", the data type

• descriptions$name, chr "SIM-CORCBM-SEED-123", the name of the dataset

• descriptions$truthTableStr, NA, truth table structure

• descriptions$design, chr "FCTRL-X-MOD", study design, factorial dataset

• descriptions$modalityID, chr "1", treatment label(s)

• descriptions$readerID, chr [1:2] "1" "2", reader labels

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

str(datasetBinned123)

RJafroc documentation built on Nov. 10, 2022, 5:45 p.m.