Describes the dimensions of MCA and variants of MCA
Identifies the variables and the categories that are the most characteristic according to each dimension obtained
by a Factor Analysis. It is inspired by
dimdesc function in
FactoMineR package (see Husson et al, 2010),
but allows to analyze variants of MCA, such as 'specific' MCA or 'class specific' MCA.
dimdesc.MCA(resmca, ncp = 3, proba = 0.05)
object of class
number of dimensions to describe (default is 3)
the significance threshold considered to characterize the dimension (default is 0.05)
The statistical indicator used for variables is square correlation ratio (R2) and the one used for categories is test-value (v.test).
Returns a list of ncp lists including:
the description of the dimensions by the categorical variables (the variables are sorted)
the description of the dimensions by each category of all the categorical variables (the categories are sorted)
Husson, F., Le, S. and Pages, J. (2010). Exploratory Multivariate Analysis by Example Using R, Chapman and Hall.
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