The relative acceptability of a food or beverage is an important data point in many different scenarios. In humans, a nine‐point category scale is typically used when the hedonic characteristics of several products are of interest. However, these scales are not consistently used by participants and therefore reliability is low. This article outlines the effectiveness of four techniques (mElo, Thurstonian modeling, Bradley–Terry, and Friedman) to calculate numerical values for products based upon their performance in a paired preference paradigm. In this study, acceptance data from four separate studies were compared to numeric scores constructed from a paired preference paradigm. In general, numeric ratings constructed from paired comparisons correlated very well with the mean overall liking ratings. The relationship between these acceptance ratings and numerical preference ratings did show to be somewhat dependent on the type of food product. This study serves as a guide to those looking to further quantify paired preference data.

中文翻译：

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配对偏好测试​​的相对可接受性估计

在许多不同的情况下，食品或饮料的相对可接受性是重要的数据点。在人类中，当几种产品的享乐特征受到关注时，通常使用九点类别量表。但是，参与者无法始终如一地使用这些量表，因此可靠性很低。本文概述了四种技术（mElo，Thurstonian建模，Bradley-Terry和Friedman）根据配对偏好范式中产品的性能计算数值的有效性。在这项研究中，将来自四个独立研究的接受数据与从成对的偏好范式构建的数字评分进行比较。通常，由成对比较构成的数字等级与平均总体喜好等级非常相关。这些接受等级和数值偏好等级之间的关系确实显示出在某种程度上取决于食品的类型。这项研究为那些希望进一步量化配对偏好数据的人提供指导。