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:[EMAIL PROTECTED] Sent: Thursday, November 13, 2008 5:00 PM To: Breton, Pierre-Jean-EXT R&D/FR Cc: r-help@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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
