Welcome...

 ...to the working unit Statistics and Psychological Methods at the University of Münster (AE Nestler). The members of our lab are interested in the advancement of statistical methods for the analysis of complex psychological data. Latest research projects cover topics such as combining the social relations model with structural equation models, advancing models to examine intra-individual variability or combining standard statistical approaches such as multilevel or structural equation models with machine learning methods (e.g., trees, boosting, ...). We are also authors or contributors to different R packages. In teaching, we provide a comprehensive B.Sc.- and M.Sc.-program in psychological methods, including lectures and courses on basic and advanced statistics.

If you are interested in writing a thesis in our lab, you can find further information here. We offer supervision of both bachelor and master theses covering both substantive and methodological research questions.

Latest News

2024-11-26

New paper in press by D. Laumann, M. Krause, ..., B. Forthmann, ... & S. Heusler in Education and Information Technologies: Mobile learning in the classroom – Should students bring mobile devices for learning, or should these be provided by schools?

2024-11-14

New paper in press by B. Forthmann, M. Beisemann, P. Doebler & R. Mutz in Scientometrics: Reliable individual differences in researcher performance capacity estimates: Evaluating productivity as explanatory variable.

2024-10-21

New paper in press by B. Forthmann, P. Doebler & R. Mutz in Scientometrics: Why summing up bibliometric indicators does not justify a composite indicator.

2024-10-18

New paper in press by C. Feybesse, B. Forthmann, F. Neto, H. Holling & E. Hatfield in Sexuality & Culture: Measuring Love Around the World: A Cross-Cultural Reliability Generalization.

2024-10-08

New paper in press by S. Nestler, A. Robitzsch, & O. Lüdtke in Structural Equations Modeling: A Multidisciplinary Journal: Fitting single- and multiple-indicator STARTS models as Dynamic Structural Equation Models.