Brockhoff, Per Bruun1; Schlich, Pascal3; Skovgaard, Ib4
1 Department of Applied Mathematics and Computer Science, Technical University of Denmark2 Statistics and Data Analysis, Department of Applied Mathematics and Computer Science, Technical University of Denmark3 National Institute for Agronomic Research4 University of Copenhagen
Scale range differences between individual assessors will often constitute a non-trivial part of the assessor-by-product interaction in sensory profile data (Brockhoff, 2003, 1998; Brockhoff and Skovgaard, 1994). We suggest a new mixed model ANOVA analysis approach, the Mixed Assessor Model (MAM) that properly takes this into account by a simple inclusion of the product averages as a covariate in the modeling and allowing the covariate regression coefficients to depend on the assessor. This gives a more powerful analysis by removing the scaling difference from the error term and proper confidence limits are deduced that include scaling difference in the error term to the proper extent. A meta study of 8619 sensory attributes from 369 sensory profile data sets from SensoBase (www.sensobase.fr) is conducted. In 45.3% of all attributes scaling heterogeneity is present (P-value <0.05). For the 33.9% of the attributes having a product difference P-value in an intermediate range by the traditional approach, the new approach resulted in a clearly more significant result for 42.3% of these cases. Overall, the new approach claimed significant product difference (P-value <0.05) for 66.1% of the attributes compared to the 60.3% of traditional approach. Still, the new, and non-symmetrical, confidence limits are more often wider than narrower compared to the classical ones: in 72.6% of all cases.
Food Quality and Preference, 2015, Vol 39, p. 156-166