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Published in:
2011 | OriginalPaper | Chapter
Multidimensional Scaling Versus Multiple Correspondence Analysis When Analyzing Categorization Data
Authors : Marine Cadoret, Sébastien Lê, Jérôme Pagès
Published in: Classification and Multivariate Analysis for Complex Data Structures
Publisher: Springer Berlin Heidelberg
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Categorization is a cognitive process in which subjects are asked to group a set of object according to their similarities. This task was used for the first time in psychology and is becoming now more and more popular in sensory analysis. Categorization data are usually analyzed by multidimensional scaling (MDS). In this article we propose an original approach based on multiple correspondence analysis (MCA); this new methodology which provides new insights on the data will be compared to one specified procedure of MDS.