Leiden University
- Brystowski, Zino: Stacked Domain Learning for Interdisciplinary Theory Development
- Kloos, Kevin: Improving the Accuracy of Aggregate Statistics with Quantification Learning
- Liu, Yuqi: Stepwise estimation approaches of growth mixture models
- Rieble, Carlotta: Early Warning Signals of Depression Onset
- Spadaccini, Giorgio: Enhancing the use and interpretation of tree-based prediction models
University of Amsterdam
- Bilici, Zeynep: Dependent effect sizes in meta-analytical structural equation modeling (MASEM)
- Boot, Jesse: Cascading Transitions in the psychosocial sciences (addiction)
- Ertekin, Seyma: Cognitive Modeling Meets Educational Data Science
- Groot, Lennert: Winner takes all: Applying MASEM with raw data”, part of the NWO VIDI research project “No data left behind. New meta-analytic structural equation models for complex data structures.
- Finneman, Adam: Theory Construction in Complex Psychological Systems
- Johansson, Annie: Optimizing Personalized Learning at Scale by Setting Up Failure for Success
- Jonge, Hannelies: Meta-Analytic Structural Equation Modeling with Group Data
- Keetelaar, Sara: Bayesian Psych:ometric Network Modelling for Longitudinal Data
- Kucharsky, Simon: Inferring cognitive strategies from eye movements: A Bayesian model-based approach
- Nak, Jason: Connecting Phenomena to Theories in Psychological Science
- Ron, de, Jill: A Formal Theory of Fear
- Sekulovski, Nikola: Bayesian Psychometric Network Modelling for Cross-sectional Data
- Van den Ende, Maarten: Computational modelling of psychological and social dynamics and urban mental health conditions
- Veldkamp, Karel: Towards Psychometrically Interpretable Neural Networks: Bridging the Gap between Latent Variable Models from Psychometrics and Neural Networks from Deep Learning
- Waaijers, Meike: AI-Assisted Network Construction Methods
- Wit, de, Kay: Defining intimidation: empirical evidence for an aggressive interpersonal phenomenon
University of Groningen
- Heister, Hannah: What is normal? Accurate norms and their use for psychological tests
- Langener, Anna: Using multimodal data to understand the social environment and its effect on wellbeing
- Linde, Maximilian: Back to Bayesics: Solving the Reproducibility Crisis in Biomedicine
- Peringa, Ilse Petra: Predicting Performance in the Complex Soccer Environment
- Petersen, Fridtjof: Stress in Action: Modeling and Predicting the effects of stress
- Stadel, Marie: Capturing a Patient’s Context: Developing experience sampling tools for personalised patient feedback in psychotherapy
- Vries, de, Klazien: What is normal? Accurate norms and their use for psychological tests
- Zhang, Yong: Quality assessment of network models in clinical research and practice using predictive accuracy analysis
University of Twente
Tilburg University
- Arena, Giuseppe: The Time is Now: Understanding Social Network Dynamics Using Relational Event Histories
- Constantin, Mihai: Tools for Aiding Empirical Research Based on Intensive Longitudinal Data
- Costantini, Eduardo: Treatment of Missing Data in High-Dimensional Social and Behavioral Science Data
- Failenschmid, Jan: Non-Linear Intensive Longitudinal Methods
- Goos, Cas: Improving the Robustness of Science using Evidence-Based Journal Level Interventions
- Kuchina, Angelina: Psychometric innovations in monitoring learning progress in students
- Le, Tra: SEM 2.0: Towards personalized multi-disciplinary treatment plans
- Liu, Anne: Correcting for selectivity in datasets
- Norouzi, Rasoul: Reasoning machine in social science
- Peereboom, Sanne: Assessing the artificial mind through natural language processing and psychometrics
- Peng, Dennis: From Degrees of Freedom to Robustness: Strengthening the Evidence Base for Psychological Interventions
- Perez Alonso, Andres: Mixture multigroup Structural Equation Modeling for comparing latent variable relations among many groups
- Rasoul Norouzi: Reasoning machine in social science
- Rüffer, Franziska: Moderator Analysis in Meta-Analysis
- Rein, Manuel: New SEM methods for validly comparing structural relations over individuals and time
- Schoenmaker, Martijn: Modeling Response Styles Behaviors in a Cross-cultural Context
- Sibbald, Lisette: Prevention is Better Than Cure: Predicting the Onset of Postpartum Depression Using Early Warning Signals
- Wong, Tsz Keung: Modelling Multiverses and Correcting for P-hacking
Utrecht University
- Andresen, Pia: Coming-of-Age of Process Research: Connecting Theory with Measurement and Modelling (OPTIMAL)
- Arts, Ingrid: Increasing MI by introducing webprobing into a BSEM
- Barragan Ibanez, Camila: Bayesian sample size calculation for trials with multilevel data
- Behbahani, Mohammad: Exploring Hidden Patterns in Relational Event History Data: an extension of Hidden Markov Model for the Relational Event Model
- Berkhout, Sophie: Intensive Longitudinal Methodology
- Carrière, Thijs: Data quality in app based data collection
- Chvojka, Edita: Rethinking Model Fit Guidelines for Longitudinal Structural Equation
Modeling (LSEM) in Research on Youth - Edmar, Alfons: Bayesian Evidence Synthesis for informative hypotheses: Aggregating evidence from conceptual replications
- Fang, Qixiang: Content Validity of High-Dimensional Measurement
- Haqiqatkhah, Manuel: Methodology of Psychological Processes
- Leplaa, Hidde: Replication in the behavioural sciences
- Lösener,Ulrich: Bayesian Sample Size Calculation for Multilevel Trials
- Mildiner Moraga, Sebastián: The multilevel explicit-duration hidden Markov model for real time behavioural data
- Moazeni, Mehran: Developing and applying machine learning algorithms to improve prediction in patients with heart failure
- Mohammadi, Hadi: Explainable NLP with Human-AI Collaboration in Social Science
- Oberman, Hanne: Computational Evaluation for Dark Data Science
- Remmerswaal, Danielle: Push-to-app: Effective recruitment and retention in smart surveys
- Sayed, Khadiga: Studies into Non-Saturated Randomized Response Models
- Sukpan, Chuenjai: Inequality-constrained model selection (for dynamical models)
- Volker, Thom: Private yet accessible: advancing privacy-aware synthetization of sensitive microdata
KU University Leuven
- Chiara Carlier
- Claesen, Aline: Methods for estimating and improving the replicability of psychological science
- Cloos, Leonie: Improving the measurement of mood and mood disorder
- Dou, Zhiwei: Statistical methods for intensive longitudinal dyadic data
- Guay, Jennifer Dang: Comparing Relations among Psychological Constructs Across Groups
- Ji, Yuanyuan: Using measurement bursts in ESM to capture affect regulation
- Kunc, Benjamin: Developing optimal experience sampling measures of psychological processes
- Lin, Tzu-Yao: Can we trust our numbers? Quantification of measurement reliability for intensive longitudinal data
- Peeters, Lisa: Developing adaptive sampling schemes for improving the design of intensive longitudinal studies.
- Pihlajamäki, Milla: The Who, How, and What of Experience Sampling – Building an Evidence-Based Methodological Foundation for Experience-Sampling Research in Different Populations
- Piot, Maarten: Improving the user experience of the innovative blended care platform m-Path
- Revol, Jordan
- Schat, Evelien: Online detection of early warning signals of mood disorder through statistical process control
- Szűcs, Tamás: Affectometrics – Examining and improving the validity of the measurement of affect
- Vermeiren, Hanke: Statistical /Psychometrical techniques for digital learning applications
- Wang, Shiyao: Statistical methods for capturing transmission and synchronization processes in triads
- Wu, Yufei: Validity of Self-Reported Affect Ratings
- Yu, Kenny
- Zhao, Hongwei: Novel mixture SEM methods for comparing structural relations among many groups
Statistics Netherlands (CBS)
VU University Amsterdam
- Gómez-Echeverry, Santiago: Measuring the Quality of Big Data and Administrative Data