Specific Correspondence Analysis for the Social Sciences
Breakdown of variance by group
Assign new labels
Average coordinates
Contribution balance
Add a new layer of points on top of an existing plot with output from ...
Add values to label
Summaries of contribution values
Cut ordinal variables
Create categories according to the quadrant position of each individua...
Multiple Class Specific Correspondence Analysis on all values in a fac...
CSA measures
Exports the labels of a soc.ca object into a csv file.
Export results from soc.ca
Extract individuals
Extract coordinates for the categories from an soc.mca
Extract supplementary categories from an soc.mca
Calculate contributions per heading
Explore the cloud of individuals
Indicator matrix
Invert the direction of coordinates
Map the active modalities
Add points to an existing map created by one of the soc.ca mapping fun...
Array of maps
Create the base of a soc.ca map
Array of several CSA maps
CSA-MCA array
Map the coordinates of the individuals in a CSA and its MCA
Map the most contributing modalities
Density plot for the cloud of individuals
Ellipse array
Concentration ellipses
Map the individuals of a soc.ca analysis
Map all modalities
Map path along an ordered variable
Map select modalities and individuals
Map the supplementary modalities
MCA Eigenvalue check
Compare MCA's with triads
Cut a continuous variable into categories with a specified minimum
Pipe operator
Print soc.ca objects
Soc.ca a package for specific correspondence analysis
Class Specific Multiple Correspondence Analysis
soc.mcasoc.mca performs a specific multiple correspondence analysis ...
Add supplementary individuals to a result object
Convert to MCA class from FactoMineR
Variance table
Check if data is valid for soc.mca
Specific and class specific multiple correspondence analysis on survey-like data. Soc.ca is optimized to the needs of the social scientist and presents easily interpretable results in near publication ready quality.