Measures of association between two datasets; Application to sensory data

•We discuss three similarity coefficients between two datasets.•We compare them on data from sensory analysis and on simulated data.•We propose an adjusted RV coefficient and discuss its interest. We review three measures of association between two datasets in view of their use in sensory data. The...

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Bibliographic Details
Published in:Food quality and preference 2015-03, Vol.40, p.116-124
Main Authors: El Ghaziri, Angélina, Qannari, El Mostafa
Format: Article
Language:English
Subjects:
Adjusted RV coefficient
Chemical and Process Engineering
Engineering Sciences
Food engineering
Life Sciences
Multivariate correlation coefficient
Permutation test
Procrustes similarity index
RV coefficient
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Summary:•We discuss three similarity coefficients between two datasets.•We compare them on data from sensory analysis and on simulated data.•We propose an adjusted RV coefficient and discuss its interest. We review three measures of association between two datasets in view of their use in sensory data. The aim is threefold: (i) to show in which situations each measure of association is appropriate, (ii) to show their properties and how they can be applied efficiently to sensory data, (iii) to compare them. The three measures of association are multivariate correlation coefficient, RV coefficient and Procrustes similarity index. A particular emphasis is put on RV coefficient since it is very popular among sensory scientists. We stress the properties and shortcomings of this coefficient and propose an adjusted RV coefficient to be used instead of RV coefficient, particularly in situations where the number of samples is small or/and the number of variables is large.
ISSN:0950-3293
1873-6343
DOI:10.1016/j.foodqual.2014.09.010