dimeta2 | R Documentation |
Computes correlation ratios (also known as eta-squared) for a list of supplementary variables of a MCA.
dimeta2(resmca, vars, dim = c(1,2))
resmca |
object of class |
vars |
a data frame of supplementary variables |
dim |
the axes for which eta2 are computed. Default is c(1,2) |
Returns a data frame with supplementary variables as rows and MCA axes as columns.
Nicolas Robette
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).
dimdescr
, dimcontrib
, dimtypicality
# 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)
# correlation ratios
dimeta2(mca, Music[, c("Gender", "Age")])
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.