Rasanga Ruwanthi wrote:> Dear List,
>
> I am new to ROC analysis and the package ROCR. I want to compute the
confidence intervals of sensitivity and specificity for a given cutoff value. I
have used the following to calculate sensitivity and specificity:
>
> data(ROCR.simple)
> pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels)
>
> se.sp <- function (cutoff, performance) {
> sens <- performance(pred,"sens")
> spec <- performance(pred,"spec")
> num.cutoff <- which.min(abs(sens at x.values[[1]] - cutoff))
> return(list(Cutoff=sens at x.values[[1]][num.cutoff], Sensitivity=sens at
y.values[[1]][num.cutoff], Specificity=spec at y.values [[1]][num.cutoff]))
> }
>
> se.sp(cutoff=0.5, pred)
>
>
> I would be grateful if someone could let me know how to get 95% CIs for
these sensitivity and specificity?
>
> Thanks vermuchch in advance.
> Rasanga
The confidence interval will be meaningless unless you pre-specified a
single cutoff without looking at the dataset. You will probably have to
use the bootstrap to penalize for the (severe) instability caused by
examining multiple cutpoints. Then you have to ask yourself why a
cutoff is needed anyway.
Frank
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--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University