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GDAtools (version 1.5)

A Toolbox for Geometric Data Analysis and More

Description

Contains functions for 'specific' Multiple Correspondence Analysis, Class Specific Analysis, Multiple Factor Analysis, 'standardized' MCA, computing and plotting structuring factors and concentration ellipses, inductive tests and others tools for Geometric Data Analysis (Le Roux & Rouanet (2005) ). It also provides functions for the translation of logit models coefficients into percentages (Deauvieau (2010) ), weighted contingency tables, an association measure for contingency tables ("Percentages of Maximum Deviation from Independence", aka PEM, see Cibois (1993) ) and some tools to measure bivariate associations between variables (phi, Cramr V, correlation coefficient, eta-squared...).

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Version

Install

install.packages('GDAtools')

Monthly Downloads

598

Version

1.5

License

GPL (>= 2)

Maintainer

Nicolas Robette

Last Published

May 17th, 2020

Functions in GDAtools (1.5)

csMCA

Performs a 'class specific' MCA
ggadd_ellipses

Adds concentration ellipses to a MCA cloud of individuals
assoc.catcont

Bivariate association
conc.ellipse

Adds concentration ellipses to a correspondence analysis graph.
burt

Computes a Burt table
contrib

Computes contributions for a correspondence analysis
condesc

Bivariate associations
Taste

Taste (data)
Music

Music (data)
indsup

Computes statistics for supplementary individuals
assoc.twocat

Bivariate association
dimvtest

Describes the test-values of a list of supplementary variables for the axes of MCA and variants of MCA
multiMCA

Performs Multiple Factor Analysis
dichotom

Dichotomizes the variables in a data frame
ggadd_supvar

Adds a categorical supplementary variable to a MCA cloud of variables
modif.rate

Computes the modified rates of variance of a correspondence analysis
dimeta2

Describes the eta2 of a list of supplementary variables for the axes of MCA and variants of MCA
getindexcat

Returns the names of the categories in a data frame
dimdesc.MCA

Describes the dimensions of MCA and variants of MCA
ggcloud_indiv

Plots MCA cloud of individuals
dimcontrib

Describes the contributions to axes for MCA and variants of MCA
speMCA

Performs a 'specific' MCA
homog.test

Computes a homogeneity test for a categorical supplementary variable
ggadd_interaction

Adds the interaction between two categorical supplementary variables to a MCA cloud of variables
pem

Computes the local and global Percentages of Maximum Deviation from Independance (PEM)
plot.stMCA

Plots 'standardized' MCA results
medoids

Computes the medoids of clusters
textindsup

Adds supplementary individuals to a MCA graph
plot.csMCA

Plots 'class specific' MCA results
ggcloud_variables

Plots MCA cloud of variables
tabcontrib

Displays the categories contributing most to axes for MCA and variants of MCA
varsup

Computes statistics for a categorical supplementary variable
plot.multiMCA

Plots Multiple Factor Analysis
plot.speMCA

Plots 'specific' MCA results
wtable

Computes a (possibly weighted) contingency table
prop.wtable

Transforms a (possibly weighted) contingency table into percentages
stMCA

Performs a 'standardized' MCA
translate.logit

Translate logit regression coefficients into percentages
textvarsup

Adds a categorical supplementary variable to a MCA graph
catdesc

Bivariate associations