R: Specific Correspondence Analysis for the Social Sciences

# Specific Correspondence Analysis for the Social Sciences

## Documentation for package ‘soc.ca’ version 0.8.2

- DESCRIPTION file
- Package NEWS

## Help Pages

soc.ca-package | Soc.ca a package for specific correspondence analysis
add.cases | Add a layer of cases (individuals) to an mca map
add.categories | Add a layer of categories (modalities) to an mca map
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.ellipse | Add a layer with concentration ellipses to an mca map.
add.ind | 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.
add.to.label | Add values to label
assign.label | Assign new labels
average.coord | Average coordinates
balance | Contribution balance
breakdown.variance | Breakdown of variance by group
contribution | Summaries of contribution values
cowboy_cut | Cut ordinal variables
create.quadrant | Create categories according to the quadrant position of each individual
csa.all | Multiple Class Specific Correspondence Analysis on all values in a factor
csa.measures | CSA measures
directors | Directors dataset
ellipses | Calculate concentraion ellipses
export | Export results from soc.ca
export.label | Exports the labels of a soc.ca object into a csv file.
extract_cases | Extract individuals
extract_cats | Extract coordinates for the categories from an soc.mca
extract_ind | Extract individuals
extract_mod | Extract coordinates for the categories from an soc.mca
extract_sup | Extract supplementary categories from an soc.mca
get.category.relations | Get and calculate the relationships and oppositions between each pair of categories
headings | Calculate contributions per heading
ind.explorer | Explore the cloud of individuals
indicator | Indicator matrix
indicator.to.long | Pivot the indicator matrix from an MCA to long format
invert | Invert the direction of coordinates
map.active | Map the active modalities
map.add | Add points to an existing map created by one of the soc.ca mapping functions.
map.array | Array of maps
map.ca.base | Create the base of a soc.ca map
map.csa.all | Array of several CSA maps
map.csa.mca | Map the coordinates of the individuals in a CSA and its MCA
map.csa.mca.array | CSA-MCA array
map.ctr | Map the most contributing modalities
map.density | Density plot for the cloud of individuals
map.ellipse | Concentration ellipses
map.ellipse.array | Ellipse array
map.ind | Map the individuals of a soc.ca analysis
map.mod | Map all modalities
map.path | Map path along an ordered variable
map.select | Map select modalities and individuals
map.sup | Map the supplementary modalities
mca.eigen.check | MCA Eigenvalue check
mca.triads | Compare MCA's with triads
min_cut | Cut a continuous variable into categories with a specified minimum
moschidis | Moschidis example
pe13 | The Field of the Danish Power Elite
political_space97 | French Political Space example
print.soc.mca | Print soc.ca objects
prune.mca | Remove unnecessary variables from an MCA
randomize.mca | Create a randomized mca on the basis of an existing mca
rename_aes | rename_aes We import this function from ggplot2 because it is not exported.
soc.ca | Soc.ca a package for specific correspondence analysis
soc.csa | Class Specific Multiple Correspondence Analysis
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.
supplementary.categories | Supplementary coordinates for a data.frame of factors
supplementary.individuals | Add supplementary individuals to a result object
taste | Taste dataset
to.MCA | Convert to MCA class from FactoMineR
variance | Variance table
what.is.x | Check if data is valid for soc.mca