supvar | R Documentation |
From MCA results, computes statistics (weights, coordinates, contributions, test-values, variances) for a categorical supplementary variable.
supvar(resmca, var)
varsup(resmca, var)
resmca |
object of class |
var |
the categorical supplementary variable. It does not need to have been used at the MCA step. |
Returns a list:
weight |
numeric vector of categories weights |
coord |
data frame of categories coordinates |
cos2 |
data frame of categories squared cosines |
var |
data frame of categories within variances, variance between and within categories and variable squared correlation ratio (eta2) |
typic |
data frame of categories typicality test statistics |
pval |
data frame of categories p-values from typicality test statistics |
cor |
data frame of categories correlation coefficients |
varsup
is softly deprecated. Please use supvar
instead.
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).
supvars
, ggadd_supvar
, ggadd_supvars
, textvarsup
, supind
# specific MCA of 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)
# computes statistics for Age supplementary variable
supvar(mca,Music$Age)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.