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Multiple Factor Analysis (MFA)
Multiple Factor Analysis (MFA) makes it possible to analyze several tables of variables simultaneously, and to obtain results, in particular, charts, that allow studying the relationship between the observations, the variables, and tables (Escofier and Pagès, 1984). Within a table, the variables must be of the same type (quantitative table, qualitative table or frequency table), but the tables can...
PLS Path Modelling
What is PLS Path Modeling? Partial Least Squares Path Modeling (PLS-PM) is a statistical approach for modeling complex multivariable relationships (structural equation models) among observed and latent variables. Since a few years, this approach has been enjoying increasing popularity in several sciences (Esposito Vinzi et al., 2007). Structural Equation Models include a number of statistical methodologies...
Redundancy analysis (RDA)
What is Redundancy Analysis Redundancy Analysis (RDA) was developed by Van den Wollenberg (1977) as an alternative to Canonical Correlation Analysis (CCorA). Redundancy Analysis allows studying the relationship between two tables of variables Y and X. While the Canonical Correlation Analysis is a symmetric method, Redundancy Analysis is non-symmetric. In Canonical Correlation Analysis, the components...
Youden Plots
What is a Youden plot? Youden (1959) developed a procedure for representing data produced by N laboratories for two similar materials A and B (they can be identical when we want to compare measurement methods, or different but expected to give identical values). The objective here is to simply identify which laboratories are problematic, either because the two measurements performed show an abnormal...
Factor analysis
What is Factor Analysis Exploratory factor analysis (or EFA) is a method that reveals the possible existence of underlying factors which give an overview of the information contained in a very large number of measured variables. The structure linking factors to variables is initially unknown and only the number of factors may be assumed. Latent factors used in Factor Analysis Three methods of extracting...
Generalized Procrustes Analysis (GPA)
When to use Generalized Procrustes Analysis Generalized Procrustean Analysis (GPA) is used in sensory data analysis prior to a Preference Mapping to reduce the scale effects and to obtain a consensual configuration. It also allows comparing the proximity between the terms that are used by different experts to describe products. Principle of Generalized Procrustes Analysis We define by configuration...
CATA data analysis
What is CATA (check-all-that-apply) analysis? CATA (check-all-that-apply) surveys have become more and more popular for sensory product characterization since 2007, when it was presented by Adams et al. CATA surveys allow to focus on consumers, more representative of the market, instead of trained assessors. They are easy to set up and easy for participants to answer. The principle is that each assessor...