Hi, using mca function in library(MASS) I obtained the following result: > miacm=mca(factor.variables,abbrev=TRUE,nf=11) > miacm Call: mca(df = factor.variables, nf = 11, abbrev = TRUE)
Multiple correspondence analysis of 1000 cases of 3 factors Correlations 0.605 0.599 0.586 0.577 0.577 0.577 0.571 0.555 0.546 0.000 0.000 cumulative % explained 30.23 60.18 89.49 118.35 147.22 176.09 204.62 232.37 259.69 259.69 259.69 Burt matrix is 12 by 12. Does anyone know how can the percentage of explained variability be greater than 100? Thank you, Stefano Cabras University of Cagliari (Italy) ______________________________________________ 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
