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Gender differences and measurement bias in the assessment of adult intelligence: Evidence from the Italian WAIS-IV and WAIS-R standardizations

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  • Pezzuti, Lina
  • Tommasi, Marco
  • Saggino, Aristide
  • Dawe, James
  • Lauriola, Marco

Abstract

Research on gender differences in intelligence has led to inconsistent results. Different methods seem to provide different estimates using the Wechsler scales. The present study analyzed WAIS-IV and WAIS-R standardization data. We assessed gender differences in subtest scores, indices, and IQs and used a Multi-Group Confirmatory Factor Analysis (MGCFA) to investigate whether gender differences were due to differences in ability factors or test bias. The larger effect sizes in favor of men were found in the Arithmetic subtest and the Working Memory Index of the WAIS-IV. Likewise, for the WAIS-R, Arithmetic, Information, and Block Design subtests and all IQ scores were the larger effect sizes. The MGCFA supported the metric invariance of both editions. For the WAIS-IV, partial scalar invariance was achieved by releasing intercept equality for Information, Comprehension, and Arithmetic. For the WAIS-R, also Coding and Digit Span intercepts had to be unconstrained. Men outperformed women on the perceptual reasoning ability factor. No gender differences were found for the processing speed factor. Men had higher working memory ability, while no difference emerged for verbal comprehension. However, the latent mean differences could be affected by a lack of scalar invariance. A comparison of observed effect sizes at the subtest level to those expected according to MGCFA revealed that Information, Arithmetic, and Comprehension subtests were gender-biased in both editions. As a whole, gender differences appeared more pronounced in the WAIS-R. Gender differences in perceptual reasoning seem genuine, as does their absence in processing speed. Implications for clinical assessment are discussed.

Suggested Citation

  • Pezzuti, Lina & Tommasi, Marco & Saggino, Aristide & Dawe, James & Lauriola, Marco, 2020. "Gender differences and measurement bias in the assessment of adult intelligence: Evidence from the Italian WAIS-IV and WAIS-R standardizations," Intelligence, Elsevier, vol. 79(C).
  • Handle: RePEc:eee:intell:v:79:y:2020:i:c:s0160289620300143
    DOI: 10.1016/j.intell.2020.101436
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    References listed on IDEAS

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    1. Francisco Parro, 2012. "International Evidence on the Gender Gap in Education over the Past Six Decades: A Puzzle and an Answer to It," Journal of Human Capital, University of Chicago Press, vol. 6(2), pages 150-185.
    2. Oberski, Daniel, 2014. "lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 57(i01).
    3. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
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    1. Giofrè, D. & Allen, K. & Toffalini, E. & Mammarella, I.C. & Caviola, S., 2022. "Decoding gender differences: Intellectual profiles of children with specific learning disabilities," Intelligence, Elsevier, vol. 90(C).

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