# [R] Calculate Specificity and Sensitivity for a given threshold value

Pierre-Jean-EXT.Breton at sanofi-aventis.com Pierre-Jean-EXT.Breton at sanofi-aventis.com
Thu Nov 13 17:59:56 CET 2008

```Hi Frank,

In fact, I don't use this for clinical research practice.
I am currently testing several scoring methods and I'd like
to know which one is the most effective and which threshold
value I should apply to discriminate positives and negatives.
So, any idea for my problem ?

Pierre-Jean

-----Original Message-----
From: Frank E Harrell Jr [mailto:f.harrell at vanderbilt.edu]
Sent: Thursday, November 13, 2008 5:00 PM
To: Breton, Pierre-Jean-EXT R&D/FR
Cc: r-help at r-project.org
Subject: Re: [R] Calculate Specificity and Sensitivity for a given
threshold value

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\$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 ?
>

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

```