A new approach for the analysis of data and the clustering of subjects in a CATA experiment. (March 2019)

• Record Type: Journal Article
• Authors: Llobell, Fabien; Cariou, Véronique; Vigneau, Evelyne; Labenne, Amaury; Qannari, El Mostafa
• Is Part Of: Food quality and preference. Volume 72(2019)
• Page Start: 31
• Page End: 39
• Publication Date: 2019-03
• Subjects: CATA data -- Correspondence analysis -- Cluster analysis -- Agreement indices -- STATIS method; 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.2018.09.006
• Languages: English
• ISSNs: 0950-3293

Abstract

Highlights: The agreement among the subjects who take part in a CATA experiment is investigated. CATATIS is a new method for the analysis of CATA data that takes account of the agreement among the subjects. CLUSCATA is a method for the segmentation of subjects involved in a CATA task. Abstract: A new approach for the analysis of the data and the clustering of the subjects in a Check All That Apply (CATA) experiment is outlined. It encompasses indices to assess the agreements among the subjects. These indices are taken into account for the analysis of the CATA data and the segmentation of the subjects. The analysis of the CATA data bears some similarities to the STATIS method and the cluster analysis of the subjects follows the same pattern as a clustering approach, called CLV, for the cluster analysis of variables, and a clustering approach, called CLUSTATIS, for clustering datasets.