Plot of attractions between categories

Adds attractions between categories, as measured by phi coefficients or percentages of maximum deviation (PEM), by plotting segments onto a MCA cloud of variables.

ggadd_attractions(p, resmca, axes = c(1,2), measure = "phi", min.asso = 0.3,
col.segment = "lightgray", col.text = "black", text.size = 3)

Arguments

p

ggplot2 object with the cloud of variables

resmca

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

axes

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

measure

character string. The measure for attractions: "phi" (default) for phi coefficients, "pem" for percentages of maximum deviation (PEM).

min.asso

numerical value ranging from 0 to 1. The minimal attraction value for segments to be plotted. Default is 0.3.

col.segment

Character string with the color of the segments. Default is lightgray.

col.text

Character string with the color of the labels of the categories. Default is black.

text.size

Size of the labels of categories. Default is 3.

Value

a ggplot2 object

References

Cibois, Philippe. Les méthodes d’analyse d’enquêtes. Nouvelle édition [en ligne]. Lyon: ENS Éditions, 2014. <http://books.openedition.org/enseditions/1443>

Author

Nicolas Robette

Examples

# specific MCA on 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)
# Plots attractions
p <- ggcloud_variables(mca, col="white", legend="none")
ggadd_attractions(p, mca, measure="phi", min.asso=0.1)