Dear Joris, thanks for your reply - it is the sem case which interests me. Suppose for example I use sem to construct a CFA for a set of variables, with a single latent variable, then this could be equivalent to a PCA with a single component, couldn't it? From the PCA I could "save" the scores as new variables; is there an equivalent with sem? This would be particularly useful if e.g. in sem I let some of the errors covary and then wanted to use the "saved scores" in some subsequent analysis.
By the way, lavaan is at cran.r-project.org/web/packages/lavaan/index.html Best Wishes Steve www.promente.org | skype stevepowell99 | +387 61 215 997 On Tue, Jun 22, 2010 at 7:08 PM, Joris Meys <jorism...@gmail.com> wrote: > 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.
