rocdor: Estimate DOR from an AUC under a Proper Model Assumption

In parodistefano/properROC: Display and Analyze Proper ROC Curves

Description

Estimate the Diagnostic Odds Ratio (DOR) corresponding to the area under a ROC curve (AUC), under the assumption of a proper model.

Usage

rocdor(auc, eps = 1e-04, MAXITER = 1000L)

Arguments

auc	The area under a ROC curve
eps	The precision required for DOR estimate (default: 0.0001)
MAXITER	the maximum number of iterations for the DOR estimate (default: 1000)

Value

dor, the Diagnostic Odds Ratio (the parameter defining a proper ROC curve)

Examples

ROCCa125 <- roctable(PancreaticData$Ca125, PancreaticData$Status)
DORCa125 <- rocdor(rocauc(ROCCa125))
print(paste("DOR for the proper ROC curve for Ca125 tumor marker: ",
      round(DORCa125,4)))

parodistefano/properROC documentation built on May 24, 2019, 6:16 p.m.