Message-ID: <200512021111.07468.s.cabras@unica.it>
Date: 2005-12-02T10:11:07Z
From: Stefano Cabras
Subject: cumulative % explained in mca() library(MASS)
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)