RocFun: ROC estimation function

In cenROC: Estimating Time-Dependent ROC Curve and AUC for Censored Data

ROC estimation function

Description

ROC estimation function

Usage

RocFun(U, D, M, bw = "NR", method, ktype)

Arguments

U	The vector of grid points where the ROC curve is estimated.
D	The event indicator.
M	The numeric vector of marker values for which the time-dependent ROC curves is computed.
bw	The bandwidth parameter for smoothing the ROC function. The possible options are NR normal reference method; PI plug-in method and CV cross-validation method. The default is the NR normal reference method.
method	is the method of ROC curve estimation. The possible options are emp emperical metod; untra smooth without boundary correction and tra is smooth ROC curve estimation with boundary correction.
ktype	A character string giving the type kernel to be used: "normal", "epanechnikov", "biweight", or "triweight".

Author(s)

Beyene K. Mehari and El Ghouch Anouar

References

Beyene, K. M. and El Ghouch A. (2020). Smoothed time-dependent receiver operating characteristic curve for right censored survival data. Statistics in Medicine. 39: 3373– 3396.

cenROC documentation built on March 31, 2023, 5:19 p.m.