Dear Kimmo, MCA is a rather old name (introduced, I think, in the 1960s by Songuist and Morgan in the OSIRIS package) for a linear model consisting entirely of factors and with only additive effects -- i.e., an ANOVA model will no interactions. You can fit such a model with lm() -- e.g., lm(y ~ f1 + f2 + etc.). Typically, the results of an MCA are reported using "adjusted means." You could compute these manually, or via the effects package.
I hope this helps, John ------------------------------ John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario, Canada web: socserv.mcmaster.ca/jfox > -----Original Message----- > From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On > Behalf Of K. Elo > Sent: June-11-08 1:07 AM > To: r-help@r-project.org > Subject: [R] MCA in R > > Hi! > > Is there any possibilities to do multiple classification analysis (MCA) > in R? (MCA examines the relationships between several categorical > independent variables and a single dependent variable, and determines > the effects of each predictor before and after adjustment for its > inter-correlations with other predictors in the analysis). > > Kind regrads, > Kimmo Elo > > --- > University of Turku, Finland > Dep. of political science > > ______________________________________________ > 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. ______________________________________________ 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.
