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soc.ca (version 0.8.1)

Specific Correspondence Analysis for the Social Sciences

Description

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.

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Install

install.packages('soc.ca')

Monthly Downloads

143

Version

0.8.1

License

GPL-3

Issues

28

Pull Requests

0

Stars

14

Forks

1

Maintainer

Anton Larsen

Last Published

August 25th, 2025

Functions in soc.ca (0.8.1)

extract_cases

Extract individuals
get.category.relations

Get and calculate the relationships and oppositions between each pair of categories
headings

Calculate contributions per heading
extract_sup

Extract supplementary categories from an soc.mca
indicator.to.long

Pivot the indicator matrix from an MCA to long format
ind.explorer

Explore the cloud of individuals
export.label

Exports the labels of a soc.ca object into a csv file.
extract_cats

Extract coordinates for the categories from an soc.mca
indicator

Indicator matrix
invert

Invert the direction of coordinates
map.csa.mca.array

CSA-MCA array
map.csa.all

Array of several CSA maps
map.ellipse

Concentration ellipses
map.ctr

Map the most contributing modalities
map.active

Map the active modalities
map.csa.mca

Map the coordinates of the individuals in a CSA and its MCA
map.add

Add points to an existing map created by one of the soc.ca mapping functions.
map.density

Density plot for the cloud of individuals
map.array

Array of maps
map.ca.base

Create the base of a soc.ca map
min_cut

Cut a continuous variable into categories with a specified minimum
map.ind

Map the individuals of a soc.ca analysis
mca.triads

Compare MCA's with triads
mca.eigen.check

MCA Eigenvalue check
map.ellipse.array

Ellipse array
map.mod

Map all modalities
map.path

Map path along an ordered variable
map.select

Map select modalities and individuals
moschidis

Moschidis example
map.sup

Map the supplementary modalities
prune.mca

Remove unnecessary variables from an MCA
soc.mca

soc.mca soc.mca performs a specific multiple correspondence analysis on a data.frame of factors, where cases are rows and columns are variables.
%>%

Pipe operator
rename_aes

rename_aes We import this function from ggplot2 because it is not exported.
randomize.mca

Create a randomized mca on the basis of an existing mca
soc.ca

Soc.ca a package for specific correspondence analysis
soc.csa

Class Specific Multiple Correspondence Analysis
print.soc.mca

Print soc.ca objects
pe13

The Field of the Danish Power Elite
political_space97

French Political Space example
supplementary.categories

Supplementary coordinates for a data.frame of factors
supplementary.individuals

Add supplementary individuals to a result object
variance

Variance table
what.is.x

Check if data is valid for soc.mca
taste

Taste dataset
to.MCA

Convert to MCA class from FactoMineR
add.ellipse

Add a layer with concentration ellipses to an mca map.
add.categories

Add a layer of categories (modalities) to an mca map
add.cases

Add a layer of cases (individuals) to an mca map
add.quadrant.labels

Annotate labels to the quadrants of an MCA or any ggplot2 based quadrant plot.
assign.label

Assign new labels
average.coord

Average coordinates
add.category.relations

Add category relations to a soc.ca plot
add.count

Add a new layer of points on top of an existing plot with output from the min_cut function
add.density

Add a layer with density curves to an mca map.
add.to.label

Add values to label
contribution

Summaries of contribution values
balance

Contribution balance
csa.all

Multiple Class Specific Correspondence Analysis on all values in a factor
ellipses

Calculate concentraion ellipses
create.quadrant

Create categories according to the quadrant position of each individual
csa.measures

CSA measures
breakdown.variance

Breakdown of variance by group
directors

Directors dataset
export

Export results from soc.ca
cowboy_cut

Cut ordinal variables