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dc.contributor.authorRicci, Cristian
dc.contributor.authorBaumgartner, Jeannine
dc.contributor.authorWentzel-Viljoen, Edelweiss
dc.contributor.authorSmuts, Cornelius M.
dc.date.accessioned2019-03-26T08:17:09Z
dc.date.available2019-03-26T08:17:09Z
dc.date.issued2019
dc.identifier.citationRicci, C. et al. 2019. Food or nutrient pattern assessment using the principal component analysis applied to food questionnaires. Pitfalls, tips and tricks. International journal of food sciences and nutrition, 70(6):738-748. [https://doi.org/10.1080/09637486.2019.1566445]en_US
dc.identifier.issn0963-7486
dc.identifier.issn1465-3478 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/32046
dc.identifier.urihttps://www.tandfonline.com/doi/full/10.1080/09637486.2019.1566445
dc.identifier.urihttps://doi.org/10.1080/09637486.2019.1566445
dc.description.abstractWe considered the Blom’s transformation, a statistical method aimed to normalise and standardise food intakes before principal component analysis. A simulation study was performed to evaluate the eigenvalue distribution of a correlation matrix under common conditions in food questionnaire analysis. The scree plot visual inspection and the Guttman–Kaiser (GK) criterion were compared to Horn’s parallel analysis to evaluate their efficacy in food pattern identification. The scree plot results as a monotone continuous series when no food patterns are present. In this situation, about 50% of the eigenvalues assume a value higher than one, showing a first fallacy of the GK. When three food patterns are simulated a clear discontinuity appears after the third eigenvalue, showing that the scree-plot visual inspection is a suitable method to identify food patterns. Finally, according to the present work it appears that the GK generates a number of false-positive food patternsen_US
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectPrincipal component analysisen_US
dc.subjectFoods/nutrients pattern recognitionen_US
dc.subjectFood intake questionnairesen_US
dc.subjectScree plot visual inspectionen_US
dc.subjectGuttman–Kaiser criterionen_US
dc.titleFood or nutrient pattern assessment using the principal component analysis applied to food questionnaires. Pitfalls, tips and tricksen_US
dc.typeArticleen_US
dc.contributor.researchID29790514 - Ricci, Cristian
dc.contributor.researchID24054909 - Baumgartner, Jeannine
dc.contributor.researchID10998497 - Wentzel-Viljoen, Edelweiss
dc.contributor.researchID20924445 - Smuts, Cornelius Mattheus


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