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.