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How to Compare Psychometric Factor and Network Models

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We f...

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Autores principales: Kan, Kees-Jan, de Jonge, Hannelies, van der Maas, Han L. J., Levine, Stephen Z., Epskamp, Sacha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709577/
https://www.ncbi.nlm.nih.gov/pubmed/33023229
http://dx.doi.org/10.3390/jintelligence8040035
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author Kan, Kees-Jan
de Jonge, Hannelies
van der Maas, Han L. J.
Levine, Stephen Z.
Epskamp, Sacha
author_facet Kan, Kees-Jan
de Jonge, Hannelies
van der Maas, Han L. J.
Levine, Stephen Z.
Epskamp, Sacha
author_sort Kan, Kees-Jan
collection PubMed
description In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples.
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spelling pubmed-77095772020-12-03 How to Compare Psychometric Factor and Network Models Kan, Kees-Jan de Jonge, Hannelies van der Maas, Han L. J. Levine, Stephen Z. Epskamp, Sacha J Intell Commentary In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples. MDPI 2020-10-02 /pmc/articles/PMC7709577/ /pubmed/33023229 http://dx.doi.org/10.3390/jintelligence8040035 Text en © 2020 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 Commentary
Kan, Kees-Jan
de Jonge, Hannelies
van der Maas, Han L. J.
Levine, Stephen Z.
Epskamp, Sacha
How to Compare Psychometric Factor and Network Models
title How to Compare Psychometric Factor and Network Models
title_full How to Compare Psychometric Factor and Network Models
title_fullStr How to Compare Psychometric Factor and Network Models
title_full_unstemmed How to Compare Psychometric Factor and Network Models
title_short How to Compare Psychometric Factor and Network Models
title_sort how to compare psychometric factor and network models
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7709577/
https://www.ncbi.nlm.nih.gov/pubmed/33023229
http://dx.doi.org/10.3390/jintelligence8040035
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