Comparison of MFA and GPA for projective mapping data

The paper “A comparison of generalised procrustes analysis and multiple factor analysis for projective mapping data” authored by O. Tomic, I. Berget and T. Næs was recently published in Food Quality and Preference.


Generalised procrustes analysis and multiple factor analysis are multivariate statistical methods that
belong to the family of multiblock methods. Both methods are often used for analysis of data from projective
mapping (a.k.a. Napping). In this study, generalised procrustes analysis and multiple factor analysis
are compared for a number of simulated and real data sets. The type of data used in this study
were (I) random data from Monte Carlo simulations; (II) constructed data that were manipulated according
to some specific criteria; (III) real data from nine Napping experiments. Focus will be on similarities of
the consensus solutions. In addition we considered interpretation of the RV coefficient and individual differences
between assessors.


Projective mapping
Generalised procrustes analysis
Multiple factor analysis
Consumer test
Multiblock method
RV coefficient