Multiple factor analysis (MFA) is an analytical method closely related to principal components analysis (PCA). MFA uses eigenvalue decomposition to transform multiple measurements on the same items into orthogonal principal components. These components can help you understand how the items are similar and how they are different. MFA uses multiple table or consensus PCA techniques.
Figure 7.1 Consensus Map in Multiple Factor Analysis