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Bayesian structural equation modeling (BSEM) offers deeper insights into the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) structure than traditional methods. A five-factor model with correlated residuals best fits the data, supporting WISC-V score interpretation.

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Area of Science:

  • Psychometrics
  • Cognitive Psychology
  • Educational Psychology

Background:

  • Traditional factor analysis methods have limitations in fully capturing complex cognitive structures.
  • Prior research favored a four-bifactor model for the WISC-V structure.
  • Bayesian structural equation modeling (BSEM) offers advanced capabilities for exploring latent variable relationships.

Purpose of the Study:

  • To investigate the theoretical structure of the WISC-V using Bayesian structural equation modeling (BSEM).
  • To compare the fit of a five-factor higher-order model against a previously preferred four-bifactor model.
  • To evaluate the utility of BSEM in advancing intelligence theory and addressing replication issues in cognitive assessment.

Main Methods:

  • Bayesian structural equation modeling (BSEM) was employed to analyze the WISC-V structure.
  • All cross-loadings and correlated residual terms were specified within the BSEM framework.
  • Model fit was compared between a proposed five-factor higher-order model and a four-bifactor model.

Main Results:

  • The five-factor higher-order model, with a correlated residual between Visual-Spatial and Fluid Reasoning, demonstrated a superior fit to the WISC-V data.
  • No other statistically significant cross-loadings or correlated residual terms were identified in the measurement model.
  • The WISC-V ten subtest primary battery achieved simple structure, supporting the manual's interpretation guidelines.

Conclusions:

  • BSEM provides a more comprehensive understanding of the WISC-V's theoretical structure compared to traditional methods.
  • The findings support the interpretation of WISC-V index scores as outlined in the official manual.
  • BSEM serves as a valuable tool for exploring complex cognitive relationships and enhancing structural validity research in psychology.