Kaliss wrote:
Hi list,
I'm new to R and I'm currently using ROCR package.
Data in input look like this:
DIAGNOSIS SCORE
1 0.387945
1 0.50405
1 0.435667
1 0.358057
1 0.583512
1 0.387945
1 0.531795
1 0.527148
0 0.526397
0 0.372935
1 0.861097
And I run the following simple code:
d <- read.table("inputFile", header=TRUE);
pred <- prediction(d$SCORE, d$DIAGNOSIS);
perf <- performance( pred, "tpr", "fpr");
plot(perf)
So building the curve works easily.
My question is: can I have the specificity and the sensitivity for
a score threshold = 0.5 (for example)? How do I compute this ?
Thank you in advance
Beware of the utility/loss function you are implicitly assuming with
this approach. It is quite oversimplified. In clinical practice the
cost of a false positive or false negative (which comes from a cost
function and the simple forward probability of a positive diagnosis,
e.g., from a basic logistic regression model if you start with a cohort
study) vary with the type of patient being diagnosed.
Frank
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
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