GDAtools (version 1.6)

dimeta2: Describes the eta2 of a list of supplementary variables for the axes of MCA and variants of MCA

Description

Computes eta2 for a list of supplementary variables. It allows to analyze variants of MCA, such as 'specific' MCA or 'class specific' MCA.

Usage

dimeta2(resmca, l, n, dim = 1:resmca$call$ncp)

Arguments

resmca

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

l

a list of supplementary variables

n

a vector of names for the supplementary variables. The vector's length must be equal to 'l''s length

dim

the axes for which eta2 are computed. Default is 1:ncp

Value

Returns a data frame with supplementary variables as rows and axes as columns.

References

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

dimdesc, dimdesc.MCA, dimcontrib, condes, speMCA, csMCA

Examples

# NOT RUN {
## Performs a specific MCA on 'Music' example data set
## ignoring every 'NA' (i.e. 'not available') categories,
## and then describes the eta2 for Gender and Age (axes 1 and 2).
data(Music)
getindexcat(Music[,1:5])
mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15))
dimeta2(mca,list(Music$Gender,Music$Age),c('Gender','Age'),dim=1:2)
# }