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

[Pierre-Jean-EXT.Breton at sanofi-aventis.com]

Hi Frank,

Thank you for your answer. 
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 <- 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