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st: Re: ROC curve for ordinal data
At 19:05 19/12/03 +0100, Roland Andersson wrote:
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 have used Robert Centors ROC analyzer for
calculating the non-parametric ROC area of even binary
The ROC area is useful when comparing the
discriminating power of diagnostic variables
independent of the incidence of the disease, even for
I think this reference can be of interest:
The Area under an ROC Curve with Limited Information
Wilbert B. van den Hout
I hope this helps.
Newson R. Parameters behind "nonparametric" statistics: Kendall's tau,
Somers' D and median differences. The Stata Journal 2002; 2(1): 45-64.
Lecturer in Medical Statistics
Department of Public Health Sciences
King's College London
5th Floor, Capital House
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Tel: 020 7848 6648 International +44 20 7848 6648
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or 020 7848 6605 International +44 20 7848 6605
Opinions expressed are those of the author, not the institution.
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