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TUTORIAL 2 –  The Analysis of Sensory Profiling Data Revisited by Scaling. Univariate and Multivariate Implications on Panel Performances and Product Differences
Presenter – Pascal Schlich

Classical analysis of sensory profiling data assumes that panelists use a comparable width of the sensory scales. Due to physiological and psychological reasons, this assumption is likely to be wrong. The Mixed Assessor Model (MAM) includes individual scaling coefficients taking into account this panel heterogeneity. We proposed recently MAM-CAP and MAM-CVA as respective extensions of CAP (Control of Assessor performances) system and CVA (Canonical Variate Analysis) taking scaling effect into account.

We developed two R-packages to support these new techniques, also easily accessible in the TimeSens® software. Thanks to the SensoBase (a database of a thousand of sensory studies), we conducted meta-analysis to investigate whether and to what extent these new methods provide different and eventually "better" results than the classical ones.

The workshop will summarize the 7 papers we published on that topic in the period 2015-2017. Then access to these techniques with the two R-package and TimeSens® will be demonstrated using real data provided by the instructor and/or brought by the participants.

The aim of this tutorial is first to introduce the theory behind these new techniques and then to demonstrate the use of the corresponding R-packages. Furthermore, these techniques are also available in the TimeSens® software which makes them easily available to panel leaders who cannot necessarily be able to play with R-packages. A brief demonstration of how to easily use them from TimeSens® will be conducted.

Intended Audience – Anyone interested in an introduction to the MAM and in an update about related techniques. Anyone willing to learn how to analyze their own data with these techniques either in R or in TimeSens®
Prerequisites – Basic knowledge about simple ANOVA will be required.
Equipment – Participants are encouraged to bring their own laptop in order to be able to play with the R-packages and/or with the TimeSens® software in the last part of the tutorial. Either they can bring their own datasets for analyzing them or they will be able to play with the ones used by the instructors during the tutorial.

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