Typicality tests for supplementary variables

Computes typicality tests for a list of supplementary variables of a MCA.

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. If 1 (default), all categories are displayed

Value

Returns a list of data frames giving the typicality 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).

Author

Nicolas Robette

See also

dimdescr, dimeta2, dimcontrib

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)
# typicality tests for gender and age
dimtypicality(mca, Music[, c("Gender", "Age")])
#> $dim.1
#>              weight test.stat p.value
#> Age.15-24        78  4.282548 0.00002
#> Gender.Men      253  0.055648 0.95562
#> Gender.Women    247 -0.055648 0.95562
#> Age.25-49       204 -0.936718 0.34890
#> Age.50+         218 -2.205306 0.02743
#> 
#> $dim.2
#>              weight test.stat p.value
#> Age.50+         218  9.834220 0.00000
#> Gender.Women    247  2.153442 0.03128
#> Gender.Men      253 -2.153442 0.03128
#> Age.25-49       204 -4.378377 0.00001
#> Age.15-24        78 -7.509471 0.00000
#>