Speaker
Description
Psychometric Network Analysis represents a cutting-edge methodology for modeling psychological phenomena as interconnected systems of variables. This approach allows for the exploration of relationships among variables across individuals and over time (Borsboom et al., 2021). The fundamental structure of a psychometric network comprises nodes, which denote variables within a dataset, and edges, representing pairwise conditional associations between node pair. The accessibility of user-friendly software in the open-source R environment have facilitated the proliferation of network psychometrics across various disciplines in the psychological and social sciences. The symposium showcases five compelling applications of psychometric network analysis across diverse fields within Psychology, including personality, cognitive, clinical, and positive psychology. Costantini will provide an overview of psychometric network analysis, illustrating its application within personality psychology. Zagaria and colleagues explore the distinctiveness of orthorexia nervosa within the spectrum of eating disorders by applying network psychometrics to cross-sectional data. Tosi employs Cross-Lagged Panel Network (CLPN) models to investigate the longitudinal changes in the relationships between cognitive functions in patients with mild cognitive impairment. Andreoli and colleagues investigate the clinical validity of the Fully Idiographic Network Analysis (FINA) by comparing the clinician’s anticipated psychological network for their patient with the patient’s empirical network estimated on Ecological Momentary Assessment data. Finally, Zambelli and colleagues applied a Meta-Analytic Gaussian Network Aggregation (MAGNA) to investigate similarities and differences among the reciprocal interrelation of flourishing components across 22 countries.
| If you're submitting a symposium, or a talk that is part of a symposium, is this a junior symposium? | No |
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