RocFun: ROC estimation function

In elghouch/cenROC: Estimation of the Time-Dependent ROC Curve and AUC for Censored Survival Data

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. (2019). Smoothed time-dependent ROC curves for right-censored survival data. <https://dial.uclouvain.be/pr/boreal/object/boreal:219643>.

elghouch/cenROC documentation built on April 2, 2020, 5:03 a.m.