Autism and Hierarchical Models of Intelligence

Michael A. Levine, Huan Chen, Ericka L. Wodka, Brian S. Caffo, Joshua B. Ewen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The Wechsler Intelligence Scale for Children (WISC) employs a hierarchical model of general intelligence in which index scores separate out different clinically-relevant aspects of intelligence; the test is designed such that index scores are statistically independent from one another within the normative sample. Whether or not the existing index scores meet the desired psychometric property of being statistically independent within autistic samples is unknown. Method: We conducted a factor analysis on WISC fifth edition (WISC-V) (N = 83) and WISC fourth edition (WISC-IV) (N = 131) subtest data in children with autism. We compared the data-driven exploratory factor analysis with the manual-derived index scores, including in a typically developing (TD) WISC-IV cohort (N = 209). Results: The WISC-IV TD cohort showed the expected 1:1 relationship between empirically derived factors and manual-derived index scores. We observed less unique correlations between our data-driven factors and manualized IQ index scores in both ASD samples (WISC-IV and WISC-V). In particular, in both WISC-IV and -V, working memory (WM) influenced index scores in autistic individuals that do not load on WM in the normative sample. Conclusions: WISC index scores do not show the desired statistical independence within autistic samples, as judged against an empirically-derived exploratory factor analysis. In particular, within the currently used WISC-V version, WM influences multiple index scores.

Original languageEnglish (US)
JournalJournal of Autism and Developmental Disorders
DOIs
StateAccepted/In press - 2023

Keywords

  • Autism
  • Factor analysis
  • Intelligence
  • IQ
  • Wechsler

ASJC Scopus subject areas

  • Developmental and Educational Psychology

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