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: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org] On
> Behalf Of K. Elo
> Sent: June-11-08 1:07 AM
> To: r-help at 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 adjus?tment for its
> inter-correlations with other predictors in the analysis).
>
> Kind regrads,
> Kimmo Elo
>
> ---
> University of Turku, Finland
> Dep. of political science
>
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