> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of João Fadista > Sent: Tuesday, April 08, 2008 3:10 PM > To: ONKELINX, Thierry; r-help@r-project.org > Subject: Re: [R] permutation test assumption? > > Dear Thierry, > > Thanks for the reply. But as you may read in the paper > http://bioinformatics.oxfordjournals.org/cgi/content/abstract/ > 22/18/2244 when the sample sizes are not the same there may > be an increase in the Type I error rate. > > Comments will be appreciated. > > Best regards, > João Fadista > > > ________________________________ > > De: ONKELINX, Thierry [mailto:[EMAIL PROTECTED] > Enviada: ter 08-04-2008 15:27 > Para: João Fadista; r-help@r-project.org > Assunto: RE: [R] permutation test assumption? > > > > Dear João, > > You can do permutation tests on an unbalanced design. > > HTH, > > Thierry >
João, I haven't read the paper, but the abstract didn't mention different sample sizes as a problem. Do the authors comment on sample size in the paper itself? If so, what did they say? If not, then why do you think sample size is a problem? Dan Daniel J. Nordlund Research and Data Analysis Washington State Department of Social and Health Services Olympia, WA 98504-5204 ______________________________________________ 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.
