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GDAtools (version 2.1)

ggadd_attractions: Plot of attractions between categories

Description

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

Usage

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

Value

a ggplot2 object

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.

Author

Nicolas Robette

References

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

See Also

ggcloud_variables

Examples

Run this code
# 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)

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