Psychometric Network Analysis and Dimensionality Assessment: A Software Review
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| Publicado en: | Education Sciences vol. 15, no. 5 (2025), p. 555 |
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| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
MDPI AG
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2076-3344 | ||
| 024 | 7 | |a 10.3390/educsci15050555 |2 doi | |
| 035 | |a 3211937071 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231457 |2 nlm | ||
| 100 | 1 | |a Qian Meihua |u College of Education, Clemson University, Clemson, SC 29634, USA | |
| 245 | 1 | |a Psychometric Network Analysis and Dimensionality Assessment: A Software Review | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Psychometric network analysis (PNA) has been gaining great popularity over the past decade. As a promising dimensionality assessment method, existing research has shown that PNA is able to outperform traditional methods such as exploratory factor analysis in examining the internal structure of a latent construct, and various R packages have been developed to carry out PNA. Yet, PNA has not been widely used in various fields due to researchers’ lack of familiarization with this method and the available R packages. Therefore, this study aims to briefly review the PNA method, compare different R packages, and provide step-by-step guidance on how to use these R packages to conduct PNA using a personality dataset. | |
| 653 | |a Associations | ||
| 653 | |a Discriminant analysis | ||
| 653 | |a Quantitative psychology | ||
| 653 | |a Software reviews | ||
| 653 | |a Social networks | ||
| 653 | |a Psychopathology | ||
| 653 | |a Variables | ||
| 653 | |a Researchers | ||
| 653 | |a Mental depression | ||
| 653 | |a Correlation | ||
| 653 | |a Depression (Psychology) | ||
| 653 | |a Psychometrics | ||
| 653 | |a Factor Analysis | ||
| 653 | |a Computer Software Reviews | ||
| 653 | |a Data Analysis | ||
| 653 | |a Fundamental Concepts | ||
| 653 | |a Network Analysis | ||
| 653 | |a Personality Studies | ||
| 653 | |a Factor Structure | ||
| 653 | |a Algorithms | ||
| 700 | 1 | |a Wang, Xianyong |u Wilbur O. and Ann Powers College of Business, Clemson University, Clemson, SC 29634, USA; xianyon@g.clemson.edu | |
| 700 | 1 | |a Dai Shenghai |u College of Education, Washington State University, Pullman, WA 99164, USA; s.dai@wsu.edu | |
| 773 | 0 | |t Education Sciences |g vol. 15, no. 5 (2025), p. 555 | |
| 786 | 0 | |d ProQuest |t Education Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3211937071/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3211937071/fulltextwithgraphics/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3211937071/fulltextPDF/embedded/75I98GEZK8WCJMPQ?source=fedsrch |