Whereas traditional correspondence analysis analyzes a table, multiple correspondence analysis analyzes the variables themselves; for example, a multi-response question with 11 categories is analyzed as 11 categorical variables. It is essentially a form of factor analysis for categorical data. You should use it when you want a general understanding of how categorical variables are related. This article describes how to run a Multiple Correspondence Analysis in Displayr.
- Multiple categorical variables to use as inputs to the Multiple Correspondence Analysis. As an example, we'll use 5 different variables from a political survey: voting in the 2008 and 2012 US elections, approval of President Trump, age, and gender.
1. From the toolbar menu, select Anything > Advanced Analysis > Dimension Reduction > Multiple Correspondence Analysis.
2. Select the categorical variable inputs from the Input Variables drop-down list in the object inspector on the right.
3. Click the Calculate button to generate the output.