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Recent Integrations of Latent Variable Network Modeling With Psychometric Models
The combination of network modeling and psychometric models has opened up exciting directions of research. However, there has been confusion surrounding differences among network models, graphic models, latent variable models and their applications in psychology. In this paper, I attempt to remedy t...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8695432/ https://www.ncbi.nlm.nih.gov/pubmed/34955989 http://dx.doi.org/10.3389/fpsyg.2021.773289 |
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author | Wang, Selena |
author_facet | Wang, Selena |
author_sort | Wang, Selena |
collection | PubMed |
description | The combination of network modeling and psychometric models has opened up exciting directions of research. However, there has been confusion surrounding differences among network models, graphic models, latent variable models and their applications in psychology. In this paper, I attempt to remedy this gap by briefly introducing latent variable network models and their recent integrations with psychometric models to psychometricians and applied psychologists. Following this introduction, I summarize developments under network psychometrics and show how graphical models under this framework can be distinguished from other network models. Every model is introduced using unified notations, and all methods are accompanied by available R packages inducive to further independent learning. |
format | Online Article Text |
id | pubmed-8695432 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86954322021-12-24 Recent Integrations of Latent Variable Network Modeling With Psychometric Models Wang, Selena Front Psychol Psychology The combination of network modeling and psychometric models has opened up exciting directions of research. However, there has been confusion surrounding differences among network models, graphic models, latent variable models and their applications in psychology. In this paper, I attempt to remedy this gap by briefly introducing latent variable network models and their recent integrations with psychometric models to psychometricians and applied psychologists. Following this introduction, I summarize developments under network psychometrics and show how graphical models under this framework can be distinguished from other network models. Every model is introduced using unified notations, and all methods are accompanied by available R packages inducive to further independent learning. Frontiers Media S.A. 2021-12-09 /pmc/articles/PMC8695432/ /pubmed/34955989 http://dx.doi.org/10.3389/fpsyg.2021.773289 Text en Copyright © 2021 Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Wang, Selena Recent Integrations of Latent Variable Network Modeling With Psychometric Models |
title | Recent Integrations of Latent Variable Network Modeling With Psychometric Models |
title_full | Recent Integrations of Latent Variable Network Modeling With Psychometric Models |
title_fullStr | Recent Integrations of Latent Variable Network Modeling With Psychometric Models |
title_full_unstemmed | Recent Integrations of Latent Variable Network Modeling With Psychometric Models |
title_short | Recent Integrations of Latent Variable Network Modeling With Psychometric Models |
title_sort | recent integrations of latent variable network modeling with psychometric models |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8695432/ https://www.ncbi.nlm.nih.gov/pubmed/34955989 http://dx.doi.org/10.3389/fpsyg.2021.773289 |
work_keys_str_mv | AT wangselena recentintegrationsoflatentvariablenetworkmodelingwithpsychometricmodels |