SubsidieMeestersA New Bayesian Foundation for Psychometric Network Modelling
This project aims to enhance psychological network modelling by developing a Bayesian confirmatory methodology with model-averaging for robust, replicable results, implemented in user-friendly software.
Projectdetails
Introduction
Network modelling is quickly gaining ground as a promising way to understand psychological phenomena. The rise of network analysis can be observed throughout the psychological sciences but has been particularly influential in psychopathology.
Methodological Challenges
While the network modelling literature has been rapidly expanding, methodological innovations struggle to keep pace. Reviews taking stock of the field invariably zoom in on the methodological challenges that network research faces. The following issues rank firmly among the field's top priorities:
- The absence of a confirmatory scheme
- The replicability of network results
- The struggle with population heterogeneity
These methodological challenges critically impede our understanding of psychological phenomena and the design of effective interventions.
Proposed Research Program
This proposal outlines a new research program for psychological network modelling that addresses current methodological challenges. Based on the basic principles of Bayesian inference, I develop a new confirmatory network methodology that uses model-averaging to deliver robust, replicable network results.
New Model-Averaging Approach
The new model-averaging approach will be designed for:
- An exhaustive collection of network models
- Cross-sectional and longitudinal applications
I will develop new models that are urgently needed—but missing from the current set of networks—and advance solutions for modelling heterogeneous psychological data to complete the new program.
Impact and Implementation
The proposed work puts psychological network modelling on a firm methodological foundation. To boost the project's impact, the new methods and models are made available in JASP (jasp-stats.org), a user-friendly, free statistical software package that I co-developed.
Armed with an exhaustive set of network models, a confirmatory methodology that delivers replicable results, and their implementation in open-source software, applied researchers can leverage the full potential of psychological network modelling.
Financiële details & Tijdlijn
Financiële details
| Subsidiebedrag | € 1.499.991 |
| Totale projectbegroting | € 1.499.991 |
Tijdlijn
| Startdatum | 1-9-2022 |
| Einddatum | 31-8-2027 |
| Subsidiejaar | 2022 |
Partners & Locaties
Projectpartners
- UNIVERSITEIT VAN AMSTERDAMpenvoerder
Land(en)
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