GDAtools (version 2.1)

ggadd_interaction: Plot of interactions between two categorical supplementary variables

Description

Adds the interactions between two categorical supplementary variables to a MCA cloud of variables

Usage

ggadd_interaction(p, resmca, v1, v2, sel1 = 1:nlevels(v1), sel2 = 1:nlevels(v2),
axes = c(1,2), textsize = 5, legend = "right")

Value

a ggplot2 object

Arguments

p

ggplot2 object with the cloud of variables

resmca

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

v1

Factor. The first categorical supplementary variable.

v2

Factor. The second categorical supplementary variable.

sel1

Numeric vector of indexes of the categories of the first supplementary variable to be used in interaction. By default, every categories are used.

sel2

Numeric vector of indexes of the categories of the second supplementary variable to be used in interaction. By default, every categories are used.

axes

numeric vector of length 2, specifying the components (axes) to plot. Default is c(1,2).

textsize

Size of the labels of categories. Default is 5.

legend

the position of legends ("none", "left", "right", "bottom", "top", or two-element numeric vector). Default is right.

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

ggcloud_variables, ggadd_supvar, ggadd_supvars, ggadd_kellipses, ggadd_ellipses, ggadd_corr, ggsmoothed_supvar, ggadd_chulls, ggadd_density

Examples

# specific MCA of Taste example data set
data(Taste)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA",
          "Comedy.NA", "Crime.NA", "Animation.NA", "SciFi.NA", "Love.NA", 
          "Musical.NA")
mca <- speMCA(Taste[,1:11], excl = junk)
# interaction between Gender and Age
p <- ggcloud_variables(mca, col = "lightgrey", shapes = FALSE)
ggadd_interaction(p, mca, Taste$Gender, Taste$Age)