Describes the contributions to axes for MCA and variants of MCA
Identifies the categories and individuals that contribute the most characteristic according to each dimension obtained by a Factor Analysis. It allows to analyze variants of MCA, such as 'specific' MCA or 'class specific' MCA.
object of class
dimensions to describe (default is c(1,2))
if FALSE, displays all the categories; if TRUE (default), displays only categories and individuals with contributions higher than average
Contributions are sorted and assigned a positive or negative sign according to the corresponding categories or individuals' coordinates, so as to facilitate interpretation.
Returns a list:
a list of categories' contributions to axes
a list of individuals' contributions to axes
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).
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