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Abstract

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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.

Details

1009240
ERIC Subject
Correlation;
Social Networks;
Depression (Psychology);
Psychometrics;
Factor Analysis;
Computer Software Reviews;
Data Analysis;
Psychopathology;
Researchers;
Fundamental Concepts;
Network Analysis;
Personality Studies;
Factor Structure;
Algorithms
Subject
Associations;
Discriminant analysis;
Quantitative psychology;
Software reviews;
Social networks;
Psychopathology;
Variables;
Researchers;
Mental depression
Business indexing term
Identifier / keyword
psychometric network analysis; dimensionality assessment; exploratory factor analysis; software review; personality
Research method
Factor analysis; Quantitative research
Title
Psychometric Network Analysis and Dimensionality Assessment: A Software Review
Author
Qian Meihua 1 ; Wang, Xianyong 2 ; Dai Shenghai 3   VIAFID ORCID Logo 

1  College of Education, Clemson University, Clemson, SC 29634, USA 
2  Wilbur O. and Ann Powers College of Business, Clemson University, Clemson, SC 29634, USA; [email protected] 
3  College of Education, Washington State University, Pullman, WA 99164, USA; [email protected] 
Publication title
Education Sciences; Basel
Volume
15
Issue
5
First page
555
Publication year
2025
Publication date
2025
Publisher
MDPI AG
Place of publication
Basel
Country of publication
Switzerland
Publication subject
Education
e-ISSN
22277102
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-04-30
Milestone dates
2025-03-03 (Received); 2025-04-26 (Accepted)
Publication history
 
 
   First posting date
30 Apr 2025
DOI
https://doi.org/10.3390/educsci15050555
ProQuest document ID
3211937071
Document URL
https://www.proquest.com/scholarly-journals/psychometric-network-analysis-dimensionality/docview/3211937071/se-2?accountid=208611
Copyright
© 2025 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 (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-05-27
Database
ProQuest One Academic