Reconciling Latent Variables and Networks: Exploring and extending the Psychometric-Toolbox
Kevin Kistermann, Vivato V. Andriamiarana, Augustin Kelava

TL;DR
This paper reviews and synthesizes connections between network psychometrics and classical psychometric models, proposing extensions to the psychometric-toolbox to foster interdisciplinary collaboration and address conceptual issues.
Contribution
It advances the psychometric-toolbox by integrating statistical methodologies from various research fields, promoting systematic development and cross-disciplinary collaboration.
Findings
Synthesized connections between network psychometrics and classical models.
Presented a visual format for methodological integration.
Highlighted opportunities for empirical research and conceptual reconciliation.
Abstract
Since the introduction of network psychometrics, several connections to statistical models in "classical" psychometrics (i.e., IRT, SEM, GLM) as well as to approaches from other research fields have been established. In this paper, these developments have been reviewed and synthesized and, based on an exploratory literature search, further advanced and presented in an accessible visual format. This perspective opens up promising opportunities to extend the psychometric-toolbox by incorporating and learning from statistical methodologies developed in other research domains, which often address similar or even identical problems. Highlighting these methodological commonalities may also foster collaboration across research fields that have traditionally remained largely independent. Moreover, awareness of these connections may render methodological development more systematic and…
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