Original scientific paper
Application of the Network Analysis in Psychological Research
APA 6th Edition
Lonza, A. (2020). Application of the Network Analysis in Psychological Research. Psihologijske teme, 29 (3), 561-588. https://doi.org/10.31820/pt.29.3.5
MLA 8th Edition
Lonza, Anamarija. "Application of the Network Analysis in Psychological Research." Psihologijske teme, vol. 29, no. 3, 2020, pp. 561-588. https://doi.org/10.31820/pt.29.3.5. Accessed 28 Sep. 2023.
Chicago 17th Edition
Lonza, Anamarija. "Application of the Network Analysis in Psychological Research." Psihologijske teme 29, no. 3 (2020): 561-588. https://doi.org/10.31820/pt.29.3.5
Lonza, A. (2020). 'Application of the Network Analysis in Psychological Research', Psihologijske teme, 29(3), pp. 561-588. https://doi.org/10.31820/pt.29.3.5
Lonza A. Application of the Network Analysis in Psychological Research. Psihologijske teme [Internet]. 2020 [cited 2023 September 28];29(3):561-588. https://doi.org/10.31820/pt.29.3.5
A. Lonza, "Application of the Network Analysis in Psychological Research", Psihologijske teme, vol.29, no. 3, pp. 561-588, 2020. [Online]. https://doi.org/10.31820/pt.29.3.5
The network approach represents a novel paradigm for exploring relations between psychological constructs and observable variables. According to this approach, variables form an autonomous dynamical system; the psychological construct is therefore not viewed as their common cause, but a result of their complex interactions. From an analytical point of view, this approach is based on network analysis — a set of procedures which models variables as nodes connected by a set of edges. This paper presents an overview of network analytical procedures. In other words, it offers a brief explanation of the methods, as well as their practical application in two separate datasets. The first dataset represents data on DASS-21 (N = 1016) and it serves to demonstrate network estimation, centrality measures calculation, community detection and network stability analyses. According to the results, the highest centrality was obtained for the depression item I felt that I had nothing to look forward to, anxiety item I felt I was close to panic, and stress item I felt that 1 was using a lot of nervous energy. As expected, nodes were grouped into three clusters, namely Depression, Anxiety and Stress. Stability analyses demonstrated limited stability of edge strength, while the stability of node centrality depended on the measure used. In the second dataset, which represents data on adolescents' attitudes towards one's body appearance, the Network Comparison Test was demonstrated by comparing male (n = 524) and female (n = 763) networks. Results showed that the two networks do not differ substantially.
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