Correspondence Analysis

Correspondence analysis (CA) is a generalized principal component analysis (PCA) tailored for the analysis of qualitative data. Originally, CA was created to analyze contingency tables, but CA is so versatile that it is now used with a lot of other data table types that contain nonnegative numbers.

CA transforms a data table into two sets of factor scores: one set for the rows and one set for the columns. The factor scores give the best representation of the similarity structure of the rows and the columns of the original data table. In addition, the factors scores can be plotted as maps, which display the essential information of the original table. In these maps, rows and columns are displayed as points whose coordinates are the factor scores ...