ggadd_interaction: Plot of interactions between two categorical supplementary...

In GDAtools: Geometric Data Analysis

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), cloud = "v", textsize = 5, lines = TRUE, dashes = TRUE, 
legend = "none", force = 1, max.overlaps = Inf)

Arguments

p	ggplot2 object with the cloud of variables or the cloud of individuals
resmca	object created with MCA, speMCA, csMCA, wcMCA, bcMCA, stMCA or multiMCA function
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).
cloud	if "v" (default), the categories are plotted in the cloud of variables. If "i", the categories are plotted in the cloud of individuals.
textsize	size of the labels of categories. Default is 5.
lines	logical. Whether to add colored lines between the points of the categories of v1. Default is TRUE.
dashes	logical. Whether to add gray dashed lines between the points of the categories of v2. Default is TRUE.
legend	the position of legends ("none", "left", "right", "bottom", "top", or two-element numeric vector). Default is none.
force	force of repulsion between overlapping text labels. Defaults to 1. If 0, labels are not repelled at all.
max.overlaps	exclude text labels that overlap too many things. Defaults to Inf, which means no labels are excluded.

Value

a ggplot2 object

Note

Lines and labels are colored according to the first variable, using the default ggplot2 palette. The palette can be customized using any scale_color_* function, such as scale_color_brewer(), scale_color_grey() or scale_color_manual().

Author(s)

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)

GDAtools documentation built on June 8, 2025, 10:08 a.m.