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OverviewPsychological network analysis (PNA) has emerged as a powerful tool for understanding the complex interplay of constructs in developmental and educational sciences. Unlike traditional models that assume relationships among variables arise from latent factors, PNA conceptualizes them as dynamic systems of interacting components. This tutorial introduces PNA's theoretical foundations, key concepts (e.g., nodes, edges, network structures), and its methodological applications using cross-sectional, longitudinal, intensive, and cohort data. Through step-by-step guidance and real-world examples, we illustrate how PNA can capture developmental changes, reveal causal structures using directed acyclic graphs, and support developmental and educational research. Special emphasis is given to practical implementation using R, including network estimation, accuracy testing, and visualization. By equipping researchers with the necessary tools to construct and interpret psychological networks, this Element provides a comprehensive framework for leveraging PNA to explore the multifaceted relationships shaping learning, motivation, and social-emotional development. Full Product DetailsAuthor: Xin Tang (Shanghai Jiao Tong University, University of Helsinki, and Tallinn University) , Jindong Zhang (University of Macau) , Yuyang Zhang (Shenzhen University) , Hye Rin Lee (University of Georgia)Publisher: Cambridge University Press Imprint: Cambridge University Press ISBN: 9781009645904ISBN 10: 1009645900 Pages: 75 Publication Date: 04 June 2026 Audience: Professional and scholarly , College/higher education , Professional & Vocational , Postgraduate, Research & Scholarly Format: Hardback Publisher's Status: Forthcoming Availability: Not yet available, will be POD This item is yet to be released. You can pre-order this item and we will dispatch it to you upon it's release. This is a print on demand item which is still yet to be released. Table of Contents1. Introduction; 2. Theoretical foundations and literature review; 3. Psychological network analysis with cross-sectional data; 4. Psychological network analysis with cohort data: a case illustration; 5. Psychological network analysis with longitudinal data; 6. Causal inference using directed acyclic graphs; 7. Discussion; 8. Conclusion; Reference.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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