Abstract Sensory profiling aims to describe the sensory characteristics of food products using a list of descriptors with a panel of trained assessors. During sensory evaluations (or any other scoring task), individual differences in the scale width effectively used by assessors (scaling effect) are regularly observed. This scaling effect was included in a statistical model, the Mixed Assessor Model (MAM). This scaling effect can be decomposed into a physiological (descriptor-specific scaling) component and a psychological (overall scaling) component. The present paper shows how to take into account both physiological and psychological scaling effects in the Canonical Variate Analysis (CVA) framework. Agreement ellipses representing the pure disagreement of the subjects (scaling effect removed) are plotted around the product means. Thus, the differences between two products can be assessed by comparing their distances to the size of their agreement ellipses. Our so-called “overall CVA” and “MAM−CVA” method were compared to CVA and Principal Component Analysis (PCA) on 334 datasets. The sensory interpretations were similar for all maps but more differences between products were observed with MAM−CVA and overall CVA. An R package is offered to produce the maps presented in this paper.

中文翻译：

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通过考虑缩放效应来增强典型变量分析

摘要 感官分析旨在通过一组经过培训的评估人员使用描述词列表来描述食品的感官特征。在感官评估（或任何其他评分任务）期间，定期观察评估者有效使用的尺度宽度（尺度效应）的个体差异。这种缩放效应包含在一个统计模型中，即混合评估模型 (MAM)。这种缩放效应可以分解为生理（特定于描述符的缩放）组件和心理（整体缩放）组件。本文展示了如何在典型变量分析 (CVA) 框架中同时考虑生理和心理尺度效应。代表受试者纯分歧的同意椭圆（去除了缩放效应）围绕乘积平均值绘制。因此，可以通过比较它们的距离与其一致椭圆的大小来评估两种产品之间的差异。我们所谓的“整体 CVA”和“MAM-CVA”方法在 334 个数据集上与 CVA 和主成分分析 (PCA) 进行了比较。所有地图的感官解释都相似，但使用 MAM-CVA 和整体 CVA 观察到产品之间的更多差异。提供了一个 R 包来生成本文中介绍的地图。