Taking individual scaling differences into account by analyzing profile data with the Mixed Assessor Model. (January 2015)

• Record Type: Journal Article
• Authors: Brockhoff, Per Bruun; Schlich, Pascal; Skovgaard, Ib
• Is Part Of: Food quality and preference. Volume 39(2015:Jan.)
• Page Start: 156
• Page End: 166
• Publication Date: 2015-01
• Subjects: Sensory profile data -- Analysis of variance -- Mixed model -- Assessor differences -- Scaling differences -- Disagreement; Food preferences -- Periodicals; Food -- Quality -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Préférences alimentaires -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Food industry and trade -- Quality control; Food preferences; Food -- Quality; Periodicals; 664
• DOI: 10.1016/j.foodqual.2014.07.005
• Languages: English
• ISSNs: 0950-3293

Abstract

Highlights: Suggests a new and improved ANOVA of sensory profile data. The method is based on a simple covariate inclusion idea. The scaling handling leads to a novel post hoc confidence band construction. The importance of this is documented by a meta study using the SensoBase. The method makes a link between mixed modeling and assessor performance analysis. Abstract: 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.