dimtypicality: Typicality tests for supplementary variables of a MCA In GDAtools: A Toolbox for Geometric Data Analysis and More

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

 `1` ```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.

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).

`dimdesc`, `dimdescr`, `dimeta2`, `dimcontrib`, `condes`, `speMCA`, `csMCA`
 ```1 2 3 4 5 6 7``` ```## 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")]) ```