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Open AccessArticle

Psychometric Network Analysis of the Hungarian WAIS

Department of Psychology, Claremont Graduate University, Claremont 91711, CA, USA
Institute of Psychology, ELTE Eotvos Lorand University, 1053 Budapest, Hungary
Author to whom correspondence should be addressed.
Received: 1 June 2019 / Revised: 19 August 2019 / Accepted: 24 August 2019 / Published: 9 September 2019
(This article belongs to the Special Issue New Methods and Assessment Approaches in Intelligence Research)
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. View Full-Text
Keywords: intelligence; Process Overlap Theory; psychometric network analysis; latent variable modeling; statistical modeling intelligence; Process Overlap Theory; psychometric network analysis; latent variable modeling; statistical modeling
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MDPI and ACS Style

Schmank, C.J.; Goring, S.A.; Kovacs, K.; Conway, A.R.A. Psychometric Network Analysis of the Hungarian WAIS. J. Intell. 2019, 7, 21.

AMA Style

Schmank CJ, Goring SA, Kovacs K, Conway ARA. Psychometric Network Analysis of the Hungarian WAIS. Journal of Intelligence. 2019; 7(3):21.

Chicago/Turabian Style

Schmank, Christopher J.; Goring, Sara A.; Kovacs, Kristof; Conway, Andrew R.A. 2019. "Psychometric Network Analysis of the Hungarian WAIS" J. Intell. 7, no. 3: 21.

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