GDAtools (version 1.7)

dimtypicality: Typicality tests for supplementary variables of a MCA

Description

Computes typicality tests for a list of supplementary variables. It allows to analyze variants of MCA, such as 'specific' MCA or 'class specific' MCA.

Usage

dimtypicality(resmca, vars, dim = c(1,2), max.pval=1)

Arguments

resmca

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

vars

a data frame of supplementary variables

dim

the axes for which typicality tests are computed. Default is c(1,2)

max.pval

only categories with a p-value lower or equal to max.pval are displayed. By default, all categories are displayed

Value

Returns a list of data frames giving the test statistics and p-values of the supplementary categories for the different axes.

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

dimdesc, dimdescr, dimeta2, dimcontrib, condes, speMCA, csMCA

Examples

# NOT RUN {
## Performs a specific MCA on 'Music' example data set
## ignoring every 'NA' (i.e. 'not available') categories,
## and then computes the typicality tests for Gender and Age (axes 1 and 2).
data(Music)
getindexcat(Music[,1:5])
mca <- speMCA(Music[,1:5],excl=c(3,6,9,12,15))
dimtypicality(mca, Music[,c("Gender","Age")])
# }