On Jun 18, 2011, at 10:48 , (Ted Harding) wrote: > To add to Jeremy's comment below: The Bartlett test is very > sensitive to non-normality in the data, so can readily give > "significant" results even for non-correlated data.
Hmm, I wouldn't bet on that. Correlation tests are usually fairly robust. More likely, it's that the null hypothesis of complete independence is rather extreme, especially in a context where you are contemplating PCA or FA. (I.e., "Of _course_ they are correlated, dummy!"). > > Ted. > > On 18-Jun-11 06:47:52, Jeremy Miles wrote: >> cortest.bartlett() in the psych package. >> >> I've never seen a non-significant Bartlett's test. >> >> Jeremy >> >> >> >> On 17 June 2011 12:43, thibault grava <thibault.gr...@gmail.com> wrote: >>> Hello Dear R user, >>> >>> I want to conduct a Principal components analysis and I need to >>> run two tests to check whether I can do it or not. I found how >>> to run the KMO test, however i cannot find an R fonction for the >>> Bartlett's test of sphericity. Does somebody know if it exists? >>> >>> Thanks for your help! >>> >>> Thibault > > -------------------------------------------------------------------- > E-Mail: (Ted Harding) <ted.hard...@wlandres.net> > Fax-to-email: +44 (0)870 094 0861 > Date: 18-Jun-11 Time: 09:48:13 > ------------------------------ XFMail ------------------------------ > > ______________________________________________ > 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. -- Peter Dalgaard Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ 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.
