About the course

About the Oxford Psychological Networks School

The Oxford Psychological Networks School (OxPNS) is a state-of-the-art course designed to provide researchers with a rigorous and practical foundation in psychological network analysis, from core principles to advanced modelling techniques. The course provides training in the understanding, application, and interpretation of a wide range of psychological network models, also referred to as psychometric or statistical networks.

This five-day course is structured to enable participants to apply network analytic methods to their own research. The programme combines conceptual instruction with hands-on, step-by-step training, equipping attendees with the theoretical understanding, practical skills, and interpretative expertise required to conduct, evaluate, and report high-quality network analytic studies.

Curriculum and Methods

The curriculum provides a comprehensive introduction to psychological networks, situating it within the broader fields of network science and complex systems research.

Participants will be trained to apply a broad range of cross-sectional network models, including gaussian and mixed graphical models (e.g. GGMs and MGMs), for applications aimed at understanding:

• Risk, resilience and protective factors through a systems-based lens
• Comorbidity and co-occurrence of different phenomena
• Group comparisons (e.g. gender, age, clinical subgroups)
• Treatment and intervention effects

The programme also covers an extensive suite of advanced dynamic network models for longitudinal data, including different vector-autoregression (VAR) models, adaptable to:

• Longitudinal panel and cohort data
• Intensive longitudinal data (e.g., daily diary, ecological momentary assessment, and experience sampling method data; EMA and ESM)
• Idiographic time-series (N = 1) data

These approaches are suitable for modelling interactions and dynamics, such as for example understanding the mechanisms underlying the onset, maintenance, and emergence of different phenomena, including feedback loops and vicious cycles.

Practical Training and Analytical Skills

Throughout the course, participants will also receive guided instruction in:

• Data preparation across data types (e.g., continuous, binary, and ordinal measurement scales)
• Model estimation and diagnostics
• Interpretation of results
• Plotting and visualisation
• Evaluating and reviewing network analytic studies
• Writing and reporting network analytic findings for publication, including training in reporting and pre-registration guidelines

A particular emphasis is placed on leveraging existing and secondary datasets, as well as on designing and collecting new data optimised for network analytic approaches.

By the end of the summer school, participants will be fully equipped to implement network analytic methods across the full research pipeline — from data preparation and modelling, to interpretation and dissemination.