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

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

Survival probability conditional to the observed data estimation for right censored 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. (2020). Smoothed time-dependent receiver operating characteristic curve for right censored survival data. Statistics in Medicine. 39: 3373– 3396.

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.

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