Deconstructing CHC

Wasserman, John D.

doi:10.1080/08957347.2019.1619563

Cited by 19 publications

(29 citation statements)

References 77 publications

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“…Cucina and Howardson (2017) offered the same conclusion in their analyses. Given the volume of evidence regarding preeminence of g variance in Wechsler scales and other intelligence tests, an annulment of the unhappy arranged marriage of the theories of Cattell–Horn and Carroll appears warranted (Canivez & Youngstrom, 2019; Wasserman, 2019).…”

Section: Discussionmentioning

confidence: 99%

Construct Validity of the German Wechsler Intelligence Scale for Children–Fifth Edition: Exploratory and Confirmatory Factor Analyses of the 15 Primary and Secondary Subtests

2020

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The latent factor structure of the German Wechsler Intelligence Scale for Children–Fifth edition (German WISC-V) was examined using complementary hierarchical exploratory factor analyses (EFAs) with Schmid and Leiman transformation and confirmatory factor analyses (CFAs) for all reported models from the German WISC-V Technical Manual and rival bifactor models using the standardization sample ( N = 1,087) correlation matrix of the 15 primary and secondary subtests. EFA results did not support a fifth factor (Fluid Reasoning). A four-factor model with the dominant general intelligence ( g) factor resembling the WISC-IV was supported by EFA. CFA results indicated the best representation was a bifactor model with four group factors, complementing EFA results. Present EFA and CFA results replicated other independent assessments of standardization and clinical samples of the United States and international versions of the WISC-V and indicated primary, if not exclusive, interpretation of the Full Scale IQ as an estimate of g.

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Section: Discussionmentioning

confidence: 99%

Construct Validity of the German Wechsler Intelligence Scale for Children–Fifth Edition: Exploratory and Confirmatory Factor Analyses of the 15 Primary and Secondary Subtests

2020

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“…Furthermore, a solid factor structure in a sample of healthy subjects is not necessarily evidence for a model's clinical utility. In fact, the CHC model has been found to be lacking in this respect (Wasserman, 2019). Future research including data from cognitively impaired individuals will be required to gather data on sensitivity and specificity.…”

Section: Discussionmentioning

confidence: 99%

“…At the very top of the hierarchy, a general factor "g" is usually specified to account for covariances between the broad abilities (Schneider and McGrew, 2018). However, the nature and even existence of g remains a point of debate (Wasserman, 2019). The CHC model features cognitive domains (i.e., broad abilities) that differ from the ones that are commonly used in neuropsychological research and practice.…”

Section: Introductionmentioning

confidence: 99%

Evidence of Validity for a Newly Developed Digital Cognitive Test Battery

et al. 2020

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Clinical practice still relies heavily on traditional paper-and-pencil testing to assess a patient's cognitive functions. Digital technology has the potential to be an efficient and powerful alternative, but for many of the existing digital tests and test batteries the psychometric properties have not been properly established. We validated a newly developed digital test battery consisting of digitized versions of conventional neuropsychological tests. Two confirmatory factor analysis models were specified: a model based on traditional neuropsychological theory and expert consensus and one based on the Cattell-Horn-Carroll (CHC) taxonomy. For both models, the outcome measures of the digital tests loaded on the cognitive domains in the same way as established in the neuropsychological literature. Interestingly, no clear distinction could be made between the CHC model and traditional neuropsychological model in terms of model fit. Taken together, these findings provide preliminary evidence for the structural validity of the digital cognitive test battery.

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“…The latter suggests that it is mainly reasoning abilities, as opposed to knowledge, that create between-subjects variance in LMR (cf. Wasserman, 2019). These findings draw into question the separation of intelligence and basic skills in the IDS-2.…”

Section: Factor Structurementioning

confidence: 99%

Measurement Invariance of the Intelligence and Development Scales–2 Across Language Versions, Gender, and Age

Grieder¹,

Timmerman²,

Visser³

et al. 2021

Preprint

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We examined the factor structure of the intelligence and basic skills domains of the Intelligence and Development Scales–2 (IDS-2) and measurement invariance across the Dutch and German versions, sex, and age with confirmatory factor analyses and local structural equation modeling of the standardization samples. Of several theoretically and empirically determined models, a second-order model with six first-order factors best represented the Dutch IDS-2 structure. Five IDS-2 factors were confirmed, but Visual Processing and Abstract Reasoning and the intelligence and basic skills domains were not separable. This final model displayed full invariance across the Dutch and German versions and partial scalar invariance across sex, and it appeared largely invariant across ages 7 to 20 years. The strong general intelligence factor and weak broad ability factors suggest individual interpretation should mainly be based on the full-scale IQ. We discuss the importance of testing multiple plausible models and implications for theory and practice.

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Deconstructing CHC

Cited by 19 publications

References 77 publications

Construct Validity of the German Wechsler Intelligence Scale for Children–Fifth Edition: Exploratory and Confirmatory Factor Analyses of the 15 Primary and Secondary Subtests

Construct Validity of the German Wechsler Intelligence Scale for Children–Fifth Edition: Exploratory and Confirmatory Factor Analyses of the 15 Primary and Secondary Subtests

Evidence of Validity for a Newly Developed Digital Cognitive Test Battery

Measurement Invariance of the Intelligence and Development Scales–2 Across Language Versions, Gender, and Age

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