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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