GDAtools (version 1.6)

contrib: Computes contributions for a correspondence analysis

Description

From MCA results, computes contributions of categories and variables to the axes and the overall cloud.

Usage

contrib(resmca)

Arguments

resmca

object of class 'MCA', 'speMCA' or 'csMCA'

Value

A list of data frames:

ctr

Data frame with the contributions of categories to axes

var.ctr

Data frame with the contributions of variables to axes

ctr.cloud

Data frame with the contributions of categories to the overall cloud

vctr.cloud

Data frame with the contributions of variables to the overall cloud

Details

The contribution of a point to an axis depends both on the distance from the point to the origin point along the axis and on the weight of the point. The contributions of points to axes are the main aid to interpretation (see Le Roux and Rouanet, 2004 and 2010).

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

MCA, speMCA, csMCA, varsup

Examples

# NOT RUN {
## Performs a specific MCA on the 'Music' example data set
## and compute contributions
data(Music)
mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15))
contrib(mca)
# }