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Psychometric Network Analysis of the Hungarian WAIS

The positive manifold—the finding that cognitive ability measures demonstrate positive correlations with one another—has led to models of intelligence that include a general cognitive ability or general intelligence (g). This view has been reinforced using factor analysis and reflective, higher-orde...

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Autores principales: Schmank, Christopher J., Goring, Sara Anne, Kovacs, Kristof, Conway, Andrew R. A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789747/
https://www.ncbi.nlm.nih.gov/pubmed/31505834
http://dx.doi.org/10.3390/jintelligence7030021
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author Schmank, Christopher J.
Goring, Sara Anne
Kovacs, Kristof
Conway, Andrew R. A.
author_facet Schmank, Christopher J.
Goring, Sara Anne
Kovacs, Kristof
Conway, Andrew R. A.
author_sort Schmank, Christopher J.
collection PubMed
description The positive manifold—the finding that cognitive ability measures demonstrate positive correlations with one another—has led to models of intelligence that include a general cognitive ability or general intelligence (g). This view has been reinforced using factor analysis and reflective, higher-order latent variable models. However, a new theory of intelligence, Process Overlap Theory (POT), posits that g is not a psychological attribute but an index of cognitive abilities that results from an interconnected network of cognitive processes. These competing theories of intelligence are compared using two different statistical modeling techniques: (a) latent variable modeling and (b) psychometric network analysis. Network models display partial correlations between pairs of observed variables that demonstrate direct relationships among observations. Secondary data analysis was conducted using the Hungarian Wechsler Adult Intelligence Scale Fourth Edition (H-WAIS-IV). The underlying structure of the H-WAIS-IV was first assessed using confirmatory factor analysis assuming a reflective, higher-order model and then reanalyzed using psychometric network analysis. The compatibility (or lack thereof) of these theoretical accounts of intelligence with the data are discussed.
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spelling pubmed-67897472019-10-16 Psychometric Network Analysis of the Hungarian WAIS Schmank, Christopher J. Goring, Sara Anne Kovacs, Kristof Conway, Andrew R. A. J Intell Article The positive manifold—the finding that cognitive ability measures demonstrate positive correlations with one another—has led to models of intelligence that include a general cognitive ability or general intelligence (g). This view has been reinforced using factor analysis and reflective, higher-order latent variable models. However, a new theory of intelligence, Process Overlap Theory (POT), posits that g is not a psychological attribute but an index of cognitive abilities that results from an interconnected network of cognitive processes. These competing theories of intelligence are compared using two different statistical modeling techniques: (a) latent variable modeling and (b) psychometric network analysis. Network models display partial correlations between pairs of observed variables that demonstrate direct relationships among observations. Secondary data analysis was conducted using the Hungarian Wechsler Adult Intelligence Scale Fourth Edition (H-WAIS-IV). The underlying structure of the H-WAIS-IV was first assessed using confirmatory factor analysis assuming a reflective, higher-order model and then reanalyzed using psychometric network analysis. The compatibility (or lack thereof) of these theoretical accounts of intelligence with the data are discussed. MDPI 2019-09-09 /pmc/articles/PMC6789747/ /pubmed/31505834 http://dx.doi.org/10.3390/jintelligence7030021 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Schmank, Christopher J.
Goring, Sara Anne
Kovacs, Kristof
Conway, Andrew R. A.
Psychometric Network Analysis of the Hungarian WAIS
title Psychometric Network Analysis of the Hungarian WAIS
title_full Psychometric Network Analysis of the Hungarian WAIS
title_fullStr Psychometric Network Analysis of the Hungarian WAIS
title_full_unstemmed Psychometric Network Analysis of the Hungarian WAIS
title_short Psychometric Network Analysis of the Hungarian WAIS
title_sort psychometric network analysis of the hungarian wais
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6789747/
https://www.ncbi.nlm.nih.gov/pubmed/31505834
http://dx.doi.org/10.3390/jintelligence7030021
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