Impact of Outliers Arising From Unintended and Unknowingly Included Subpopulations on the Decisions About the Number of Factors in Exploratory Factor Analysis

Bibliographic Data

ID20283144
AuthorsYan Liu (0000-0002-1612-779X, University of British Columbia, Vancouver, British Columbia, Canada), Bruno D Zumbo (0000-0003-2885-5724, University of British Columbia, Vancouver, British Columbia, Canada)
Year2012
Volume72
Issue3
Pages388-414
Publication date2012-06-01
Open AccessYes
TypeARTICLE
VenueEducational and Psychological Measurement (JOURNAL)
Journal identifiersISSN: 0013-1644 • E-ISSN: 1552-3888
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/0013164411429821
OpenAlexW2151034533
LanguageEN
References cited22

There is a lack of research on the effects of outliers on the decisions about the number of factors to retain in an exploratory factor analysis, especially for outliers arising from unintended and unknowingly included subpopulations. The purpose of the present research was to investigate how outliers from an unintended and unknowingly included subpopulation affected the decisions about the number of factors to retain using four commonly used methods separately. The results showed that all the decision methods could provide biased results and the number of factors could be inflated, deflated, or remain the same depending on the decision methods used and outlier conditions. The findings also revealed that symmetric outliers did not affect the three principal component analysis–based methods but affected chi-square (ML) sequential tests. Finally, sample size did not play a role in the effect of outliers

Affect (linguistics) · Econometrics · Exploratory factor analysis · Outlier · Principal component analysis · Psychometrics · Sample (material) · Statistics · Advanced Statistical Methods and Models · Chemistry · Mathematics · Psychology · Sensory Analysis and Statistical Methods · Statistical Methods and Applications

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