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Psihologija
2013, vol. 46, br. 3, str. 331-347
jezik rada: engleski
vrsta rada: originalan članak
objavljeno: 04/10/2013
doi: 10.2298/PSI130801008Z
Impact of different conditions on accuracy of five rules for principal components retention
(naslov ne postoji na srpskom)
Univerzitet u Beogradu, Filozofski fakultet, Odeljenje za psihologiju

e-adresa: azoric@gmail.com

Sažetak

(ne postoji na srpskom)
Polemics about criteria for nontrivial principal components are still present in the literature. Finding of a lot of papers, is that the most frequently used Guttman Kaiser's criterion has very poor performance. In the last three years some new criteria were proposed. In this Monte Carlo experiment we aimed to investigate the impact that sample size, number of analyzed variables, number of supposed factors and proportion of error variance have on the accuracy of analyzed criteria for principal components retention. We compared the following criteria: Bartlett's χ2 test, Horn's Parallel Analysis, Guttman-Kaiser's eigenvalue over one, Velicer's MAP and CHull originally proposed by Ceulemans & Kiers. Factors were systematically combined resulting in 690 different combinations. A total of 138,000 simulations were performed. Novelty in this research is systematic variation of the error variance. Performed simulations showed that, in favorable research conditions, all analyzed criteria work properly. Bartlett's and Horns criterion expressed the robustness in most of analyzed situations. Velicer's MAP had the best accuracy in situations with small number of subjects and high number of variables. Results confirm earlier findings of Guttman-Kaiser's criterion having the worse performance.

Ključne reči

principal component analysis; criterion for extraction; factor retention

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