A comparison of generalised procrustes analysis and multiple factor analysis for projective mapping data
Peer reviewed, Journal article
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OriginalversjonFood Quality and Preference. 2015, 43 34-46. 10.1016/j.foodqual.2015.02.004
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.