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st: Re: ROC curve for ordinal data


From   Roger Newson <roger.newson@kcl.ac.uk>
To   statalist@hsphsun2.harvard.edu
Subject   st: Re: ROC curve for ordinal data
Date   Fri, 19 Dec 2003 18:24:01 +0000

At 19:05 19/12/03 +0100, Roland Andersson wrote:
I have used Robert Centors ROC analyzer for
calculating the non-parametric ROC area of even binary
diagnostic values.

The ROC area is useful when comparing the
discriminating power of diagnostic variables
independent of the incidence of the disease, even for
binary variables.

I think this reference can be of interest:
The Area under an ROC Curve with Limited Information
Wilbert B. van den Hout
Another reference, which explains why the ROC area is a good measure of predictive power for general continuous and discrete predictor variables, is my own Stata Journal article (Newson 2002). A pre-publication draft of this can be downloaded from my website (see my signature below). The article contains an example of calculating confidence limits in Stata for the difference between 2 ROC areas for 2 different "continuous" predictors and the same binary disease outcome. The method used there will work equally well for binary and other "non-continuous" predictors.

I hope this helps.

Roger

References

Newson R. Parameters behind "nonparametric" statistics: Kendall's tau, Somers' D and median differences. The Stata Journal 2002; 2(1): 45-64.


--
Roger Newson
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
5th Floor, Capital House
42 Weston Street
London SE1 3QD
United Kingdom

Tel: 020 7848 6648 International +44 20 7848 6648
Fax: 020 7848 6620 International +44 20 7848 6620
or 020 7848 6605 International +44 20 7848 6605
Email: roger.newson@kcl.ac.uk
Website: http://www.kcl-phs.org.uk/rogernewson

Opinions expressed are those of the author, not the institution.

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