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    ABSTRACT: The purpose of this study is to investigate the problem of clustering subjects in a free sorting task. We compare different measures of agreement between partitions. From a simulation study, we advocate using the Adjusted Rand index. On the basis of this index, we propose a technique for determining a consensus partition as a summary of the initial partitions given by the subjects after a categorization task. Thereafter, the problem of clustering the subjects is explored. For this purpose, a method combining hierarchical clustering and a partitioning algorithm is described. These techniques are applied to a case study of the perception of wine aromas by a panel of subjects.
    No preview · Article · Mar 2014 · Food Quality and Preference
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    ABSTRACT: The adjusted Rand index is widely used in connection with the free sorting task to assess the degree of association between two partitions of a set of stimuli. A hypothesis testing framework regarding the significance of this index is set up. It consists in a permutation test which involves the simulation of a large number of partitions from the original two partitions being compared. However, since this strategy of analysis may be time consuming, an alternative method is also proposed. It is based on statistical properties regarding the distribution of the values generated by the procedure of permutation. The two strategies of analysis are illustrated and compared on the basis of free sorting data and a simulation study.
    No preview · Article · Mar 2014 · Food Quality and Preference
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    ABSTRACT: In sensory analysis, preference mapping covers several modeling techniques applied to hedonic data for a better understanding of consumers’ liking and product optimization. External preference mapping aims at relating consumers’ hedonic data to sensory data in order to identify liking drivers. Classically, preference mapping proceeds in two steps: the first step consists in defining the perceptual space on which preference data are regressed and, the second step, identifies the predictive model according to this perceptual space. The strategy of analysis (quadratic PLS regression) presented herein fits within the framework of PLS regression. An optimal perceptual space is sought by taking account of the linear and the quadratic relationships between hedonic and sensory data. Quadratic PLS is compared to other methods of analysis on the basis of a case study related to coffee data.
    Full-text · Article · Mar 2014 · Food Quality and Preference


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