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<p>The present study examined individual differences in 24 measures of cognitive ability in a sample of young adults (<i>N</i> = 255). Each measure was completed twice, separated by a period of 2&#xa0;weeks, to assess test–retest reliability and retesting (i.e., practice) effects. Latent variable modeling was used to assess the convergent and discriminant validity of the measures, as they were selected to measure seven different cognitive constructs (attention control, processing speed, working memory, primary memory, secondary memory, fluid intelligence, and spatial ability). The measures showed adequate to high intrasession and intersession reliability. Construct-level estimates were highly reliable, and the measurement structure was invariant across the two testing occasions. In several instances, correlations among latent variables warranted further testing to ensure adequate discriminability. Finally, latent state-trait modeling indicated that the majority of systematic variance in cognitive measures is due to latent traits, rather than state-specific or task-specific factors. We discuss the practical and theoretical implications of these findings.</p>

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A comprehensive psychometrics of cognitive ability measures: Reliability, practice effects, and the stability of latent factor structures across retesting

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月29日

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  • Matthew K. Robison,
  • Stephen Campbell,
  • Lauren D. Garner,
  • Ciara Sibley,
  • Joseph Coyne

摘要

The present study examined individual differences in 24 measures of cognitive ability in a sample of young adults (N = 255). Each measure was completed twice, separated by a period of 2 weeks, to assess test–retest reliability and retesting (i.e., practice) effects. Latent variable modeling was used to assess the convergent and discriminant validity of the measures, as they were selected to measure seven different cognitive constructs (attention control, processing speed, working memory, primary memory, secondary memory, fluid intelligence, and spatial ability). The measures showed adequate to high intrasession and intersession reliability. Construct-level estimates were highly reliable, and the measurement structure was invariant across the two testing occasions. In several instances, correlations among latent variables warranted further testing to ensure adequate discriminability. Finally, latent state-trait modeling indicated that the majority of systematic variance in cognitive measures is due to latent traits, rather than state-specific or task-specific factors. We discuss the practical and theoretical implications of these findings.