Using Fit Statistic Differences to Determine the Optimal Number of Factors to Retain in an Exploratory Factor Analysis.

Educational and Psychological Measurement
W Holmes Finch

Abstract

Exploratory factor analysis (EFA) is widely used by researchers in the social sciences to characterize the latent structure underlying a set of observed indicator variables. One of the primary issues that must be resolved when conducting an EFA is determination of the number of factors to retain. There exist a large number of statistical tools designed to address this question, with none being universally optimal across applications. Recently, researchers have investigated the use of model fit indices that are commonly used in the conduct of confirmatory factor analysis to determine the number of factors to retain in EFA. These results have yielded mixed results, appearing to be effective when used in conjunction with normally distributed indicators, but not being as effective for categorical indicators. The purpose of this simulation study was to compare the performance of difference values for several fit indices as a method for identifying the optimal number of factors to retain in an EFA, with parallel analysis, which is one of the most reliable such extant methods. Results of the simulation demonstrated that the use of fit index difference values outperformed parallel analysis for categorical indicators, and for normally d...Continue Reading

References

Apr 4, 2007·Psychological Methods·R J Wirth, Michael C Edwards
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Feb 19, 2013·Structural Equation Modeling : a Multidisciplinary Journal·Xiaoxiao Tong, Peter M Bentler
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Citations

Mar 5, 2021·Frontiers in Psychology·Pablo NájeraMiguel A Sorrel
Oct 3, 2020·Research in Social & Administrative Pharmacy : RSAP·Taylor L WattersonMichelle A Chui
Jul 8, 2021·Revista latino-americana de enfermagem·Fábio Luiz MialheFlávio Rebustini

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Software Mentioned

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