Csurv: Survival probability conditional to the observed data...

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

Description

Survival probability conditional to the observed data estimation for right censored data.

Usage

Csurv(Y, M, censor, t, h = NULL, kernel = "normal")

Arguments

Y	The numeric vector of event-times or observed times.
M	The numeric vector of marker values for which we want to compute the time-dependent ROC curves.
censor	The censoring indicator, 1 if event, 0 otherwise.
t	A scaler time point at which we want to compute the time-dependent ROC curve.
h	A scaler for the bandwidth of Beran's weight calculaions. The defualt is using the method of Sheather and Jones (1991).
kernel	A character string giving the type kernel to be used: "normal", "epanechnikov", , "tricube", "boxcar", "triangular", or "quartic". The defaults is "normal" kernel density.

Value

Return a vectors:

positive P(T<t|Y,censor,M).

negative P(T>t|Y,censor,M).

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>.

Li, Liang, Bo Hu and Tom Greene (2018). A simple method to estimate the time-dependent receiver operating characteristic curve and the area under the curve with right censored data, Statistical Methods in Medical Research, 27(8): 2264-2278.

Pablo Martínez-Camblor and Gustavo F. Bayón and Sonia Pérez-Fernández (2016). Cumulative/dynamic roc curve estimation, Journal of Statistical Computation and Simulation, 86(17): 3582-3594.

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