crosstab() : Displays pretty 2, 3 or 4-way
cross-tabulations, from possibly weighted data, and with the opportunity
to color the cells of the table according to a local measure of
association (phi coefficients, standardized residuals or PEM).cattab() : Bivariate statistics between a categorical
variable and a set of variablescontab() : Bivariate statistics between a continuous
variable and a set of variablesregtab() : Univariate and multivariate regressions and
their average marginal effects side-by-sideweighted.cramer() : Cramer’s V measure of association
between two (possibly weighted) categorical variablesstdres.table() : Standardized and adjusted residuals of
a (possibly weighted) contingency tableprofiles() : bug fix when stat = “cprop” and mar =
TRUEassoc.xx() : Bivariate association measures between
pairs of variablesassoc.twocat.by() : Groupwise version of
assoc.twocat()assoc.twocont.by() : Groupwise version of
assoc.twocont()assoc.catcont.by() : Groupwise version of
assoc.catcont()profiles() : Profiles by level of a categorical
variableassoc.catcont() : new items in the results (summary
statistics, test-values)assoc.twocat() : new item in the results (p-values of
adjusted standardized residuals)ggassoc_marimekko() : y axis labels are now
horizontalcondesc() and catdesc() : labels of the
results have been renamed ; dec argument is replaced by digits and
simplified ; permutation p-values can be provided for variables and
categoriesweighted.cor2() : weighted correlations between the
columns of a data frameweighted.cov() : weighted covarianceweighted.cov2() : weighted covariances between the
columns of a data frameggpattern package moved from Imports to SuggestsMany functions in descriptio are imported from
GDAtools (1.8), with some changes and improvements, among
which the main ones are :