dimcontrib: Description of the contributions to axes

In GDAtools: Geometric Data Analysis

Description of the contributions to axes

Description

Identifies the categories and individuals that contribute the most to each dimension obtained by a Multiple Correspondence Analysis.

Usage

dimcontrib(resmca, dim = c(1,2), best = TRUE)

Arguments

resmca	object of class MCA, speMCA, or csMCA
dim	numerical vector of the dimensions to describe (default is c(1,2))
best	logical. If FALSE, displays all the categories. If TRUE (default), displays only categories and individuals with contributions higher than average

Details

Contributions are sorted and assigned a positive or negative sign according to the corresponding categories or individuals coordinates, so as to facilitate interpretation.

Value

Returns a list with the following items :

var	a list of categories contributions to axes
ind	a list of individuals contributions to axes

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

tabcontrib, dimdescr, dimeta2, dimtypicality

Examples

# specific MCA on Music example data set
data(Music)
junk <- c("FrenchPop.NA", "Rap.NA", "Rock.NA", "Jazz.NA", "Classical.NA")
mca <- speMCA(Music[,1:5], excl = junk)
# contributions to axes 1 and 2
dimcontrib(mca)

GDAtools documentation built on Oct. 6, 2023, 5:07 p.m.