GDAtools (version 1.7)

modif.rate: Computes Benzecri's modified rates of variance of a MCA

Description

Computes the modified rates of variance of a multiple correspondence analysis.

Usage

modif.rate(resmca)

Arguments

resmca

object of class MCA, speMCA, csMCA, stMCA or multiMCA

Value

Returns a data frame with 2 variables:

mrate

Numeric vector of modified rates

cum.mrate

Numeric vector of cumulative modified rates

Details

As MCA clouds often have a high dimensionality, the variance rates of the first principle axes may be quite low, which makes them hard to interpret. Benzecri (1992, p.412) proposed to use modified rates to better appreciate the relative importance of the principal axes.

References

Benzecri J.P., Correspondence analysis handbook, New-York: Dekker (1992).

Le Roux B. and Rouanet H., Multiple Correspondence Analysis, SAGE, Series: Quantitative Applications in the Social Sciences, Volume 163, CA:Thousand Oaks (2010).

Le Roux B. and Rouanet H., Geometric Data Analysis: From Correspondence Analysis to Stuctured Data Analysis, Kluwer Academic Publishers, Dordrecht (June 2004).

See Also

MCA, speMCA, csMCA

Examples

# NOT RUN {
## Computes the modified rates of variance
## of the MCA of 'Music' example data set
data(Music)
mca <- speMCA(Music[,1:5])
modif.rate(mca)
# }