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Statistical analysis of hierarchical sorting data

Abstract : Hierarchical sorting is a data collection methodology used in sensory analysis, which consists in asking people to provide a succession of categorization tasks: in the first step, they have to divide the set of objects into groups and in the second step, they can, if they want, subdivide these groups into finer groups, etc., until they judge the final groups of objects to be homogeneous. This article describes a new methodology to analyze these data: multiple factor analysis (MFA). MFA allows balancing the part of each subject into the analysis according to the number of subdivisions provided. MFA provides usual factor analytic representations (object representations) and specific representations (in particular subject representations and levels of hierarchy representations). This method is illustrated with an example in which 89 children performed a hierarchical sorting task on 16 cards. It is conducted with the R SensoMineR package.
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Submitted on : Tuesday, April 3, 2012 - 3:20:36 PM
Last modification on : Tuesday, October 19, 2021 - 10:48:08 AM

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Marine Cadoret, Sébastien Lê, Jérome Pagès. Statistical analysis of hierarchical sorting data. Journal of Sensory Studies, Wiley, 2011, 26 (2), pp.96-105. ⟨10.1111/j.1745-459X.2010.00326.x⟩. ⟨hal-00684940⟩

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