This session presents methodological advances for modeling dynamic processes in intensive longitudinal data, including dynamic network models, hidden Markov models, dynamic structural equation models, and state-space approaches.

• Dynamic latent factor Poisson network model for longitudinal relational data

  Rosa Gentile (University of Palermo, Italy)

• Estimation Accuracy of Subject-Specific Effects in the Multilevel Hidden Markov Model

  Pepijn Vink (Utrecht University, The Netherlands)

• Simultaneously capturing and characterizing states and fluctuations in intensive longitudinal data

  Dr. Jessica Schaaf (Donders Institute/Radboud UMC, Netherlands)

• Three-Step State Space Mixture Modeling to Compare Dynamic Processes Across Many Individuals

  Manuel Rein (Tilburg University, The Netherlands)

Session 2 — Methods and Applications for Intensive Longitudinal Data

This session focuses on methodological challenges and applications in experience sampling and intensive longitudinal data, highlighting new modeling approaches and applied research in behavioral science.

• Analyzing Skewed ESM Data

  Anastasiia Galkina (Maastricht University, the Netherlands)

• Deep Generalised Mixed Effects Models: a Novel Neural Network Structure for Analysing Hierarchical Data

  Nina van Gerwen (Erasmus University Medical Center, The Netherlands)

• Taking a Sledgehammer to Crack a Nut: Analyzing the Dynamics of Auditory Distraction Using Multigroup Multilevel Structural Equation Modeling

  Salome Keintzel (University of Kassel, Germany)

• The interplay between problematic gambling and biopsychosocial risk and protective factors: a dynamic network approach

  Ladan Esmalian Khamsehv (University of Bergen, Norway)

Session 3 — Latent and Applied Longitudinal Multilevel Models

This session highlights latent variable and longitudinal modeling approaches applied to health, behavioral, and population data, demonstrating the flexibility of multilevel models across diverse substantive domains.

• Predicting intersectional inequalities: MAIHDA vs. Descriptive Statistics

  Prof. dr. George Leckie (University of Bristol, United Kingdom)

• Prediction of latent disease status in a multivariate longitudinal model on Duchenne Muscular Dystrophy patients

  Chiara Degan (Leiden University Medical Center, The Netherlands)

• Identifying anomalously high abundance in highly seasonal populations of the common house mosquito in the Netherlands

  Lukas Sprengers (Netherlands Food and Consumer Product Safety Authority, The Netherlands)

• Multilevel multinomial time series models with applications to population health issues in Australasia

  Prof. dr. Alice Richardson (Australian National University, Australia)

• Predicting Distal Outcomes from Latent Classes in The Growth Mixture Models: Robustness over Various Coding of Time

  Yuqi Liu (Leiden University, The Netherlands)

Poster Session & Drinks