GDAtools (version 2.1)

dimeta2: Correlation ratios (aka eta-squared) of supplementary variables

Description

Computes correlation ratios (also known as eta-squared) for a list of supplementary variables of a MCA.

Usage

dimeta2(resmca, vars, dim = c(1,2))

Value

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

Arguments

resmca

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

vars

a data frame of supplementary variables

dim

the axes for which eta2 are computed. Default is c(1,2)

Author

Nicolas Robette

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

dimdescr, dimcontrib, dimtypicality

Examples

# specific MCA on Music example data set
data(Music)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA")
mca <- speMCA(Music[,1:5], excl = junk)
# correlation ratios
dimeta2(mca, Music[, c("Gender", "Age")])