On Aug 11, 2011, at 5:50 AM, Karl Knoblick wrote:

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,....

If you want the binomial choice situation then the AUC is not the right place to start. You should be looking at sample size calculations for logistic regression (or maybe even binom.test if you have no covariates that matter.)

--
David Winsemius

--

Would be great if somebody has a solution!

Karl



----- Ursprüngliche Mail ----
Von: Greg Snow <greg.s...@imail.org>
An: Karl Knoblick <karlknobl...@yahoo.de>; "r-h...@stat.math.ethz.ch"
<r-h...@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.s...@imail.org
801.408.8111


-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Karl Knoblick
Sent: Monday, August 08, 2011 3:29 PM
To: r-h...@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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