hi all, In the library ‘ade4’, there are two eigenanalysis which enable the ordination of the categorical variables.
1- Multiple Correspondence Analysis (MCA, Tenenhaus & Young 1985) performs the multiple correspondence analysis of a factor table (see the function ‘dudi.acm’). this function is equivalent to functions mca of the library(MASS) 2- the “mixed factorial analysis” (Hill & Smith 1976) enables the ordination of tables mixing quantitative variables and factors (functions ‘dudi.mix’ or ‘dudi.hillsmith’). I hope this helps, P.BADY At 15:47 21/04/2005 -0500, Chris Bergstresser wrote: >Hi all -- > > I'm running a Factor Analysis on my dataset, and I've located the > "factanal()" and "princomp()" methods. I don't want to do a PCA, so it > looks like I should use factanal(), but factanal() requires specifying > the number of factors you expect from the analysis. > Are there any packages out there explicitly for Exploratory Factor > Analysis that do not require specifying the number of expected factors? > >-- Chris > >______________________________________________ >R-help@stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Pierre BADY <°)))))>< Université Claude Bernard Lyon 1 UMR CNRS 5023, LEHF bat Alphonse Forel 43 boulevard du 11 novembre 1918 F-69622 VILLEURBANNE CEDEX FRANCE TEL : +33 (0)4 72 44 62 34 FAX : +33 (0)4 72 43 28 92 MEL : [EMAIL PROTECTED] http://limnologie.univ-lyon1.fr http://pierre.bady.free.fr (in construction) [[alternative HTML version deleted]] ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
