Multiple Factor Analysis

Analyze Agreement among Panelists

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 

Contents

Overview of the Multiple Factor Analysis Platform

Example of Multiple Factor Analysis

Launch the Multiple Factor Analysis Platform

Data Format

The Multiple Factor Analysis Report

Summary Plots

Consensus Map

Multiple Factor Analysis Platform Options

Statistical Details for the Multiple Factor Analysis Platform