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Prof. Dr. Manuel Völkle

The Psychological Research Methods Group deals with the development and adaptation of new assessment procedures, the statistical-mathematical modeling of psychological processes, the design of studies, as well as the analysis and interpretation of empirical-psychological data. In short, the group develops the 'tools' for describing, explaining, predicting, and possibly modifying, human experience and behavior. 

The group has special expertise in the analysis of longitudinal data for both large panel data sets (large sample, few measurement times) and ambulatory assessment data (small sample, many measurement times). The group made various contributions to the advancement and dissemination of continuous time dynamic models. 

A second focus is research on the so-called 'ergodicity' problem, that is, essentially the question to what extent findings at group level can be transferred to individuals and vice versa. 

A third focus is on causal inference with observational data and evaluation research. They use frequentist and Bayesian methods for confirmatory modeling as well as methods from the field of data mining and machine learning. Methodological research in the Voelkle Group often forms the basis for applications and methodological developments in other areas.

  • Continuous Time Dynamic Modeling
  • Structural Equation Modeling
  • Mixed Modeling

Current position

2015 - present  Full Professor of Psychological Research Methods at the Humboldt-Universität zu Berlin (DE)

Academic Education

2008 Doctoral Degree in Psychology at the Univeristät Mannheim (DE)
2004 Diploma in Psychology at the Univeristät Mannheim (DE)

DFG-funded projects

2023 - present DFG Research Grant - “Definition and estimation of causal effects in latent state trait models (CaST)”
2015 - 2020 DFG Research Grant - “The Role of Affective Flexibility in Human Development and its Contribution to Long-Term Developmental Adaptation”
2012 - 2019 DFG Research Grant - “Development of intra-subject variability of processing speed”

Selected publications

  • Orzek JH, Voelkle MC. Regularized continuous time structural equation models: A network perspective. Psychol Methods. 2023 Jan 12. doi: 10.1037/met0000550. 
  • Gische C, Voelkle MC. Beyond the Mean: A Flexible Framework for Studying Causal Effects Using Linear Models. Psychometrika. 2022 Sep;87(3):868-901. doi: 10.1007/s11336-021-09811-z.
  • Arnold M, Oberski DL, Brandmaier AM, Voelkle MC. Identifying heterogeneity in dynamic panel models with individual parameter contribution regression. Structural Equation Modeling. 2020 Jul;27(4): 613–628. doi:10.1080/10705511.2019.1667240
  • Voelkle MC, Gische C, Driver CC, Lindenberger U. The Role of Time in the Quest for Understanding Psychological Mechanisms. Multivariate Behav Res. 2018 Nov-Dec;53(6):782-805. doi: 10.1080/00273171.2018.1496813.
  • Voelkle MC, Oud JH. Continuous time modelling with individually varying time intervals for oscillating and non-oscillating processes. Br J Math Stat Psychol. 2013 Feb;66(1):103-26. doi: 10.1111/j.2044-8317.2012.02043.x.