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Multi-group and hierarchical confirmatory factor analysis of the Wechsler Intelligence Scale for Children—Fifth Edition: What does it measure?

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  • Reynolds, Matthew R.
  • Keith, Timothy Z.

Abstract

The purpose of this research was to test the consistency in measurement of Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014) constructs across the 6 through 16 age span and to understand the constructs measured by the WISC-V. First-order, higher-order, and bifactor confirmatory factor models were used. Results were compared with two recent studies using higher-order and bifactor exploratory factor analysis (Canivez, Watkins, & Dombrowski, 2015; Dombrowski, Canivez, Watkins, & Beaujean, 2015) and two using confirmatory factor analysis (Canivez, Watkins, & Dombrowski, 2016; Chen, Zhang, Raiford, Zhu, & Weiss, 2015). We found evidence of age-invariance for the constructs measured by the WISC-V. Further, both g and five distinct broad abilities (Verbal Comprehension, Visual Spatial Ability, Fluid Reasoning, Working Memory, and Processing Speed) were needed to explain the covariances among WISC-V subtests, although Fluid Reasoning was nearly equivalent to g. These findings were consistent whether a higher-order or a bifactor hierarchical model was used, but they were somewhat inconsistent with factor analyses from the prior studies. We found a correlation between Fluid Reasoning and Visual Spatial factors beyond a general factor (g) and that Arithmetic was primarily a direct indicator of g. Composite scores from the WISC-V correlated well with their corresponding underlying factors. For those concerned about the fewer numbers of subtests in the Full Scale IQ, the model implied relation between g and the FSIQ was very strong.

Suggested Citation

  • Reynolds, Matthew R. & Keith, Timothy Z., 2017. "Multi-group and hierarchical confirmatory factor analysis of the Wechsler Intelligence Scale for Children—Fifth Edition: What does it measure?," Intelligence, Elsevier, vol. 62(C), pages 31-47.
  • Handle: RePEc:eee:intell:v:62:y:2017:i:c:p:31-47
    DOI: 10.1016/j.intell.2017.02.005
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    References listed on IDEAS

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    1. William Meredith, 1993. "Measurement invariance, factor analysis and factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 525-543, December.
    2. John Schmid & John Leiman, 1957. "The development of hierarchical factor solutions," Psychometrika, Springer;The Psychometric Society, vol. 22(1), pages 53-61, March.
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    Cited by:

    1. Bryan, Victoria M. & Mayer, John D., 2020. "A meta-analysis of the correlations among broad intelligences: Understanding their relations," Intelligence, Elsevier, vol. 81(C).
    2. Caemmerer, Jacqueline M. & Maddocks, Danika L.S. & Keith, Timothy Z. & Reynolds, Matthew R., 2018. "Effects of cognitive abilities on child and youth academic achievement: Evidence from the WISC-V and WIAT-III," Intelligence, Elsevier, vol. 68(C), pages 6-20.
    3. Niileksela, Christopher R. & Reynolds, Matthew R., 2019. "Enduring the tests of age and time: Wechsler constructs across versions and revisions," Intelligence, Elsevier, vol. 77(C).
    4. Giofrè, David & Pastore, Massimiliano & Cornoldi, Cesare & Toffalini, Enrico, 2019. "Lumpers vs. splitters: Intelligence in children with specific learning disorders," Intelligence, Elsevier, vol. 76(C), pages 1-1.
    5. Caemmerer, Jacqueline M. & Keith, Timothy Z. & Reynolds, Matthew R., 2020. "Beyond individual intelligence tests: Application of Cattell-Horn-Carroll Theory," Intelligence, Elsevier, vol. 79(C).

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