David Goretzko

Dr. David Goretzko is an Assistant Professor in the Department of Methodology and Statistics at Utrecht University's Faculty of Social and Behavioural Sciences. He leads the Measurement and Machine Learning Lab and specializes in the integration of data science techniques with psychometric theory.

His academic journey includes:

• Ph.D. in Psychological Methods from LMU Munich (2020)
• M.Sc. in Statistics from LMU Munich (2018)
• M.Sc. in Psychology from LMU Munich (2016)
• B.Sc. in Physics from LMU Munich (2015)
• B.Sc. in Psychology from LMU Munich (2014)

Dr. Goretzko's research primarily focuses on the intersection of machine learning and psychometrics. His work addresses critical challenges in factor analysis, measurement invariance, and model fit assessment. He develops innovative methods that combine traditional psychometric approaches with modern data science techniques, particularly in the areas of exploratory factor analysis trees, regularized factor analysis, and cost-sensitive machine learning applications in psychological assessment. His research has significant implications for improving the validity and reliability of psychological measurements across diverse populations.

His recent publications reveal a strong trend toward integrating machine learning methodologies with traditional psychometric approaches. A significant portion of his work focuses on factor analysis techniques, particularly addressing the challenge of determining the appropriate number of factors. His research also extensively covers measurement invariance testing across multiple covariates using tree-based approaches, and he has made notable contributions to evaluating model fit in confirmatory factor analysis. The interdisciplinary nature of his work spans psychology, statistics, and computer science.

Dr. Goretzko serves as an Associate Editor for the European Journal of Psychological Assessment and is an active reviewer for numerous prestigious journals including Psychological Methods, Behavior Research Methods, and Structural Equation Modeling. He also reviews grant proposals for major funding agencies such as the German Research Foundation (DFG), National Science Foundation (NSF), and Dutch Research Council (NWO).

He currently holds a Project Grant from the German Research Foundation (DFG GO 3499/1-1) since 2021. His research program focuses on developing and validating new methodologies for psychological assessment that incorporate machine learning techniques while maintaining psychometric rigor. His work has practical applications in educational measurement, clinical psychology, and organizational assessment.

Dr. Goretzko leads the Measurement and Machine Learning Lab at Utrecht University, which focuses on developing innovative methodologies that bridge the gap between traditional psychometrics and modern data science. The lab's research has particular relevance for improving measurement practices in cross-cultural research, educational assessment, and clinical psychology settings where measurement invariance and factor structure validation are critical concerns.