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IDENTIFYING ASSESSOR DIFFERENCES IN WEIGHTING THE UNDERLYING SENSORY DIMENSIONS
Author(s) -
QANNARI EL MOSTAFA,
MEYNERS MICHAEL
Publication year - 2001
Publication title -
journal of sensory studies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.61
H-Index - 53
eISSN - 1745-459X
pISSN - 0887-8250
DOI - 10.1111/j.1745-459x.2001.tb00316.x
Subject(s) - principal component analysis , weighting , merge (version control) , mathematics , multidimensional scaling , simple (philosophy) , computer science , overweight , statistics , data mining , information retrieval , medicine , philosophy , epistemology , radiology , obesity
In a previous paper Kunert and Qannari (1999) discussed a simple alternative to Generalized Procrustes Analysis to analyze data derived from a sensory profiling study. After simple pretreatments of the individual data matrices, they propose to merge the data sets together and undergo Principal Components Analysis of the matrix thus formed. On the basis of two data sets, it was shown that the results slightly differ from those obtained by means of Generalized Procrustes Analysis. In this paper we give a mathematical justification to this approach by relating it to a statistical regression model. Furthermore, we obtain additional information from this method concerning the dimensions used by the assessors as well as the contribution of each assessor to the determination of these dimensions. This information may be useful to characterize the performance of the assessors and single out those assessors who downweight or overweight some dimensions. In particular, those assessors who overweight the last dimensions should arouse suspicion regarding their performance as, in general, the last dimensions in a principal components analysis are deemed to reflect random fluctuations.