Print Email Facebook Twitter Common factor analysis versus principal component analysis: a comparison of loadings by means of simulations Title Common factor analysis versus principal component analysis: a comparison of loadings by means of simulations Author de Winter, J.C.F. (TU Delft Biomechatronics & Human-Machine Control) Dodou, D. (TU Delft Medical Instruments & Bio-Inspired Technology) Date 2016 Abstract Common factor analysis (CFA) and principal component analysis (PCA) are widely used multivariate techniques. Using simulations, we compared CFA with PCA loadings for distortions of a perfect cluster configuration. Results showed that nonzero PCA loadings were higher and more stable than nonzero CFA loadings. Compared to CFA loadings, PCA loadings correlated weakly with the true factor loadings for underextraction, overextraction, and heterogeneous loadings within factors. The pattern of differences between CFA and PCA was consistent across sample sizes, levels of loadings, principal axis factoring versus maximum likelihood factor analysis, and blind versus target rotation. To reference this document use: http://resolver.tudelft.nl/uuid:4de36040-3502-4f2d-bc9c-3e3b563833e8 DOI https://doi.org/10.1080/03610918.2013.862274 Embargo date 2016-05-18 ISSN 0361-0918 Source Communications in Statistics: Simulation and Computation, 45 (1), 299-321 Bibliographical note Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type journal article Rights © 2016 J.C.F. de Winter, D. Dodou Files PDF Common_Factor_Analysis_ve ... ations.pdf 721.66 KB Close viewer /islandora/object/uuid:4de36040-3502-4f2d-bc9c-3e3b563833e8/datastream/OBJ/view