Description Usage Arguments Details Value Author(s) References See Also Examples
The function is a wrapper for the survivalROC.C
function in order to compute sensitivity and specificity for a binary classification of survival data.
1 2  td.sens.spec(cl, surv.time, surv.event, time, span = 0, sampling = FALSE,
na.rm = FALSE, ...)

cl 
vector of binary classes. 
surv.time 
vector of times to event occurrence. 
surv.event 
vector of event occurrence indicators. 
time 
time point for sensitivity and specificity estimations. 
span 
Span for the NNE. Default value is 0. 
sampling 
jackknife procedure to estimate the standard error of sensitivity and specificity estimations. 
na.rm 

... 
additional arguments to be passed to the 
Only NNE method is used to estimate sensitivity and specificity (see survivalROC.C
). The standard error for sensitivity and specificity is estimated through jackknife procedure (see jackknife
).
sens 
sensitivity estimate 
sens.se 
standard error for sensitivity estimate 
spec 
specificity estimate 
spec.se 
standard error for specificity estimate 
Benjamin HaibeKains
Heagerty, P. J. and Lumley, T. L. and Pepe, M. S. (2000) "TimeDependent ROC Curves for Censored Survival Data and a Diagnostic Marker", Biometrics, 56, pages 337–344.
Efron, B. and Tibshirani, R. (1986). "The Bootstrap Method for standard errors, confidence intervals, and other measures of statistical accuracy", Statistical Science, 1 (1), pages 1–35.
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Loading required package: survival
Loading required package: prodlim
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