Identifying assessor differences in weighting the underlying sensory dimensions

dc.contributor.authorMeyners, Michaelde
dc.contributor.authorQannari, El Mostafade
dc.date.accessioned2004-12-06T18:43:59Z
dc.date.available2004-12-06T18:43:59Z
dc.date.issued2000de
dc.description.abstractIn 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.en
dc.format.extent360017 bytes
dc.format.extent43061 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.urihttp://hdl.handle.net/2003/5074
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-15170
dc.language.isoende
dc.publisherUniversitätsbibliothek Dortmundde
dc.subject.ddc310de
dc.titleIdentifying assessor differences in weighting the underlying sensory dimensionsen
dc.typeTextde
dc.type.publicationtypereporten
dcterms.accessRightsopen access

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