Network analysis in psychological research with application and interpretation of R software

Document Type : Original Article

Author

Department of Psychology, Tarbiat Modares University, Tehran, Iran.

Abstract

Network analysis is an advanced statistical and graphical method which visualizes the relationship between multiple variables. The purpose of this research is to describe the analysis of computational psychological networks. Psychological network analysis helps researchers find the most important variables and relationships in a complex system. The latest estimation tools included accuracy using Bootstrap method, the degree of stability of focal indices, linkage comparison in psychological networks, and estimated indices. In addition, two new statistical methods called stationary correlation coefficient and the bootstrapped difference test were presented to compare edge-weights difference and focal indices. The statistical population of the research included 368 (120 male and 248 female) students of Tehran universities in the academic year of 2019-20. Then the anxiety of participants was measured. Network analysis using R showed that nodes 3, 6 and 11 are the most important nodes and the relationships between nodes 12-18 and 17-18 had the strongest positive relationships. Bootstrap method showed that the parameters and focal indicators of the network provide the correct estimation. The practical and interpretive steps of the mentioned theoretical foundations were presented in practical formats with anxiety data using R statistical software. The design of this article is based on theoretical and practical implications

Keywords

References

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