caCorr

<p>Name of the dataset (in dataframe format).</p>

data

<p>This function calculates the strength of the correlation between
rows and columns of the contingency table. A reference line indicates the
threshold above which the correlation can be considered important.</p>

Allows to plot a number of information related to the interpretation of Correspondence Analysis' results. It provides the facility to plot the contribution of rows and columns categories to the principal dimensions, the quality of points display on selected dimensions, the correlation of row and column categories to selected dimensions, etc. It also allows to assess which dimension(s) is important for the data structure interpretation by means of different statistics and tests. The package also offers the facility to plot the permuted distribution of the table total inertia as well as of the inertia accounted for by pairs of selected dimensions. Different facilities are also provided that aim to produce interpretation-oriented scatterplots. Reference: Alberti 2015 <doi:10.1016/j.softx.2015.07.001>.

Gianmarco Alberti

caCorr: Chart of correlation between rows and columns categories

Description

Usage

Arguments

Examples