Thanks, but 1) as input for the sample size estimation ony an AUC is given - and the output of the study should be an AUC, too. So I thought this should be the right way.
2) I read e.g. in PASS they are doing a sample size calculation for AUC. Are thesy wrong? Sorry for asking further more but I am confused a little.... Karl ----- Ursprüngliche Mail ---- Von: David Winsemius <dwinsem...@comcast.net> An: Karl Knoblick <karlknobl...@yahoo.de> CC: Greg Snow <greg.s...@imail.org>; "r-h...@stat.math.ethz.ch" <r-h...@stat.math.ethz.ch> Gesendet: Samstag, den 13. August 2011, 2:18:37 Uhr Betreff: Re: [R] Sample size AUC for ROC curves 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 >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting- >> guide.html >> and provide commented, minimal, self-contained, reproducible code. > > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
