ArticleEuropean journal of investigation in health, psychology and education2025
Psychometric Network Model Recovery: The Effect of Sample Size, Number of Items, and Number of Nodes.
Article in European journal of investigation in health, psychology and education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- The role of fatigue and sleep quality in the link between pain severity, perceived injustice and pain catastrophizing in breast cancer survivors with pain: a network analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Identification of adaptation subgroups among Chinese nursing students: an integrated latent profile and network intervention simulation analysis.BMC nursing · 2026Article
- A Network Analysis of Alexithymia, Interoception, Empathy, Self-Awareness and Psychopathological Symptoms in Young People With Autism Spectrum Disorder.Autism research : official journal of the International Society for Autism Research · 2026Article
- Characterizing emotion dynamics in remitted depression: A network approach using ecological momentary assessment.Journal of mood and anxiety disorders · 2026Article
- Network based associations between peer rejection and adolescent depression: evidence from general population and clinical samples.BMC psychology · 2026Article
- Network analysis of core symptom changes in hepatocellular carcinoma survivors after transarterial chemoembolization: A longitudinal study.Frontiers in oncology · 2026Article
- Article
- Meritocracy in Brazil, China and USA: identifying inconsistencies in the Preference for the Merit Principle Scale through Exploratory Graph Analysis.Frontiers in sociology · 2026Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In recent years, network psychometrics has emerged as an alternative to the reflective latent variable model. This model conceptualizes traits as complex systems of behaviors mutually interacting with each other. Although this model offers important advantages compared to the reflective model, questions remain regarding the necessary sample size and the influence of factors such as the number of nodes and edges. This study aims to evaluate the psychometric network model performance under different conditions of sample size, number of nodes, and number of edges. The methodology involved a simulation with 1000 replicates for each combination of sample size, number of nodes, and the value of gamma parameter, which is used to determine the magnitude of the edges considered significant. The effect of these conditions on the accuracy of edge estimations and centrality indices (strength and expected influence) was assessed using sensitivity, specificity, and bias indicators. Results suggest that sample size and network complexity have a more significant impact than
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.