GDAtools (version 1.0)

plot.stMCA: Plots 'standardized' MCA results

Description

Plots a 'standardized' Multiple Correspondence Analysis (resulting from stMCA function), i.e. the clouds of individuals or categories.

Usage

## S3 method for class 'stMCA':
plot(x, type = "v", axes = 1:2, points = "all", groups=NULL, 
                            col = "dodgerblue4", app = 0, \dots)

Details

A category is considered to be one of the most correlated to a given axis if its test-value is higher then 2.58 (which corresponds to a 0.05 threshold).

References

Robette, Bry and Roueff, 2014, "Un dialogue de sourds dans le theatre statistique? Analyse geometrique des donnees et effets de structure", forthcoming

See Also

stMCA, textvarsup, conc.ellipse

Examples

## Performs a standardized MCA on 'Music' example data set
## ignoring every 'NA' (i.e. 'not available') categories 
## and controlling for age,
## and then draws the cloud of categories.
data(Music)
mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15))
stmca <- stMCA(mca,control=list(Music$Age))
plot(stmca)
plot(stmca,axes=c(2,3),points='best',col='darkred',app=1)