Research

Our lab works at the interface of mathematical psychology, psychometrics and experimental psychology. We develop statistical models that mathematically represent cognitive processes. A particular focus of the lab is to quantify individual differences in cognition.
The modeling approach we use most is hierarchical Bayesian modeling. These models are very flexible and allow us to formalize psychometric theory and cognitive theory.
In terms of content, we are mainly interested in attentional control, perception, memory and reasoning. We strive for transparency in our research and provide data, code and open access to all manuscripts.

• Reliability and validity of individual differences in cognitive tasks
• Reliable and valid assessment of individual differences in attentional control
• Individual differences in the interpretation of quantifiers (e.g., more than x% of the points are blue)
• Bayes factors for linear models
• Development of cognitive abilities at primary school age

The transparency of the research process is very important to us. Therefore, we strive to make as many aspects of our research open and verifiable as possible. For all our research projects (and as much as possible) we make data, code for statistical analysis and manuscripts publicly available.

• Code and reproducible manuscripts can be found on github
• Data, preregistrations and code for collaboration projects can be found in the Open Science Framework

For more information on our approach, you can view a workshop designed by J. Haaf.