GDAtools v1.5

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A Toolbox for Geometric Data Analysis and More

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) <doi:10.1007/1-4020-2236-0>). It also provides functions for the translation of logit models coefficients into percentages (Deauvieau (2010) <doi:10.1177/0759106309352586>), weighted contingency tables, an association measure for contingency tables ("Percentages of Maximum Deviation from Independence", aka PEM, see Cibois (1993) <doi:10.1177/075910639304000103>) and some tools to measure bivariate associations between variables (phi, Cram<c3><a9>r V, correlation coefficient, eta-squared...).

Functions in GDAtools

Name Description
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
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Details

Type Package
Date 2020-05-14
License GPL (>= 2)
URL http://nicolas.robette.free.fr/outils_eng.html
NeedsCompilation no
Packaged 2020-05-17 10:37:30 UTC; nrobette
Repository CRAN
Date/Publication 2020-05-17 22:40:05 UTC

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