Correspondence Analysis – CA – is an exploratory multivariate method for exploring and visualizing contingency tables, i.e. tables on which a chi-squared test can be performed. CA is particularly useful in text mining.

The function Factoshiny of the package Factoshiny allows you to perform CA in an easy way. You can include extras information, manage missing data, draw and improve the graph interactively, have several numeric indicators as outputs, perform clustering on the CA results, and even have an automatic interpretation of the results. Finally, the function returns the lines of code to parameterize the analysis and redo the graphs, which makes the analysis reproducible.

Implementation with R software

See this video and the audio transcription of this video:

The lines of code to do a Correspondence Analysis:

install.packages(Factoshiny)
library(Factoshiny)
data(children)
result <- Factoshiny(children)

Course videos

Theorectical and practical informations on Correspondence Analysis are available in these 6 course videos:

1. Introduction
2. Visualizing the row and column clouds
3. Inertia and percentage of inertia
4. Simultaneous representation
5. Interpretation aids
6. Text mining with correspondence analysis

Here are the slides and the audio transcription of the course.

Materials

Here is the material used in the videos:

• Nobel data: the data set – Rmarkdown – the script with the outputs
• Birth data: the data set – Rmarkdown – the script with the outputs

Follow this link if you want to see more methods on Exploratory Data Analysis.