Construct Explication through Factor or Component Analysis: A Review and Evaluation of Alternative Procedures for Determining the Number of Factors or Components

By Wayne F. Velicer, C. Eaton, J. Fava. 2000

909 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4e1d6f9e3c736602a496b24c204add78d3d1f772

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In Computer Networks and Communications

In Management Science and Operations Research

In Statistics and Probability

Citations in the corpus

Accuracy of the Parallel Analysis Procedure With Polychoric Correlations (2009, background): “Second, contrary to some previous findings (Horn, 1965; Hubbard & Allen, 1987; Humphreys & Montanelli, 1975; Velicer et al., 2000; Zwick & Velicer, 1986) the pattern of results from the three- and eight-factor models was found to be similar.”
Evaluating a proposed modification of the Guttman rule for determining the number of factors in an exploratory factor analysis (2014, methodology): “This poor performance of the Guttman rule is consistent with prior simulation studies on factor decision methods (e.g., Hakstian et al., 1982; Velicer et al., 2000; Zwick & Velicer, 1982, 1986).”
Performance of Velicer’s Minimum Average Partial Factor Retention Method With Categorical Variables (2011, methodology): “Additionally, 4 variables per factor is just over the minimum of 3 that is required for factor identification (Widaman, 1993), 8 can be considered as a moderately strong factor (Velicer et al., 2000), and 12 as a highly overidentified factor (Widaman, 1993).”
The Authentic Personality: A Theoretical and Empirical Conceptualization and the Development of the Authenticity Scale (2008, methodology): “In studies using simulated data, Velicer, Eaton, and Fava (2000) and Zwick and Velicer (1986) demonstrated that parallel analysis and the MAP method produced more accurate decisions regarding the number of factors to retain than did examination of the scree plot or the Kaiser eigenvalue 1 criterion.”
Validation of the Measure of Revised Reinforcement Sensitivity Theory Constructs (2014, methodology): “Eigenvalue > 1 criterion, Scree test, parallel analysis and original Velicer's MAP test (O'Connor, 2000; Velicer et al., 2000) were all in favor of a threecomponent solution.”
Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research (2016, methodology): “Thus, in such situations, parallel analysis, MAP and comparing different number of factors via BIC perform bad, in average, proving that estimating the number of factors is still a non-trivial task, in spite of the past decades’ developments.”
Factor Structure of the Wechsler Intelligence Scale for Children–Fourth Edition Among Referred Students (2006, methodology): “Following the advice of Velicer, Eaton, and Fava (2000) and Henson and Roberts (in press), minimum average partials (MAP; Velicer, 1976) and parallel analysis (Horn, 1965), supplemented by a visual scree test (Cattell, 1966), were used to determine the number of factors to retain for rotation.”
Character strengths and well-being in Croatia: An empirical investigation of structure and correlates (2010, methodology): “To provide a preliminary guide in specifying the number of factors, a second-order principal component analysis of the 24 strengths was performed, according to the procedure recommended by Velicer, Eaton, and Fava (2000).”
Conceptualizing gratitude and appreciation as a unitary personality trait (2008, neutral): “Monte Carlo analyses by Velicer, Eaton, and Fava (2000) and Zwick and Velicer (1986) have shown that of all of the criteria for deciding on the number of factors to extract (e.g. scree plot, Kaiser criterion), parallel analysis and MAP provide the most accurate results.”
Connecting the STEM dots: measuring the effect of an integrated engineering design intervention (2014, methodology): “2004), and the minimum average partial revised criteria (Velicer 1976; Velicer et al. 2000), were used to determine the number of factors (Henson and Roberts 2006).”
Exploratory Factor Analysis: A Guide to Best Practice (2018, methodology): “Following the advice of Velicer et al. (2000), parallel analysis (Horn, 1965), MAP (Velicer, 1976), and the visual scree test (Cattell, 1966) were used to determine the appropriate number of factors to retain.”