[R] Sample size AUC for ROC curves

[Karl Knoblick]

Thanks. Actually I thought of something like 
Hanley JA, McNeil BJ. A method of comparing the areas under receiver operating 
characteristic curves derived from the same cases. Radiology. 1983; 148: 
839–843.
http://radiology.rsna.org/content/148/3/839.full.pdf+html
 
Has anybody R-code for this or something similar but newer?
 
The question is just easy - How many subjects do I need if I want to show that 
my diagnostic test is not only a game of dice. Data for input are the epected 
AUC, alpha and beta,....
 
Would be great if somebody has a solution!
 
Karl



----- Ursprüngliche Mail ----
Von: Greg Snow <Greg.Snow at imail.org>
An: Karl Knoblick <karlknoblich at yahoo.de>; "r-help at stat.math.ethz.ch" 
<r-help at stat.math.ethz.ch>
Gesendet: Dienstag, den 9. August 2011, 19:45:12 Uhr
Betreff: RE: [R] Sample size AUC for ROC curves

If you know how to generate random data that represents your null hypothesis 
(chance, auc=0.5) and how to do your analysis, then you can do this by 
simulation, simulate a dataset at a given sample size, analyze it, repeat a 
bunch of times and see if that sample size is about the right size.  If not, do 
it again with a different sample size until you find one that works for you.

-- 
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.snow at imail.org
801.408.8111


> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Karl Knoblick
> Sent: Monday, August 08, 2011 3:29 PM
> To: r-help at stat.math.ethz.ch
> Subject: [R] Sample size AUC for ROC curves
> 
> Hallo!
> 
> Does anybody know a way to calculate the sample size for comparing AUC
> of ROC
> curves against 'by chance' with AUC=0.5 (and/or against anothe AUC)?
> 
> Thanks!
> Karl
> 
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