PCA and factor analysis is implemented in the core R distribution, no extra packages needed. When using princomp, they're in the object.
pr.c <- princomp(USArrests,scale=T) pr.c$scores # gives you the scores see ?princomp When using factanal, you can ask for regression scores or Bartlett scorse. See ?factanal. Mind you, you will get different -i.e. more correct- results than those obtained by SPSS. I don't understand what you mean with scores in the context of structural equation modelling. Lavaan is unknown to me. Cheers Joris On Tue, Jun 22, 2010 at 3:11 PM, Steve Powell <st...@promente.net> wrote: > Dear expeRts, > sorry for such a newbie question - > in PCA/factor analysis e.g. in SPSS it is possible to save scores from the > factors. Is it analogously possible to "save" the implied scores from the > latent variables in a measurement model or structural model e.g. using the > sem or lavaan packages, to use in further analyses? > Best wishes > Steve Powell > > www.promente.org | skype stevepowell99 | +387 61 215 997 > > ______________________________________________ > 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. > -- Joris Meys Statistical consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php ______________________________________________ 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.
