Further education programmes at institutes
The section refers here to regular further education programmes at institutes:
University of Tübingen:
The Methods Centre at the University of Tübingen regularly offers further training in the form of workshops during the Fall and Spring School. The interdisciplinary workshops are aimed in particular at researchers from the fields of methodology and data science and include advanced topics such as machine learning, latent variable modelling and mixed methods. Further information can be found here: Website
University of Zurich:
A regular range of introductory and advanced courses on statistical data analysis and programming with the open-source software R: http://www.zhrcourses.uzh.ch
University of Koblenz-Landau:
A regular range of workshops on R as well as multilevel analysis and structural equation modelling: https://www.uni-koblenz-landau.de/de/methodenzentrum/fortbildung
Institute for Quality Development in Education:
https://www.iqb.hu-berlin.de/fdz/workshops
We would also like to draw your attention to the following colleagues who can be contacted regarding further education programmes.
Further education programmes on request
| Contact person and university | Main foci |
|---|---|
| Prof. Dr. Michael Eid | Linear structural equation modelling, change measurement with latent variables, multitrait-multimethod analysis, analysis of multi-rater data, latent class analysis, test construction and analysis |
| Dr. Georg Hosoya | Introduction to multilevel analysis with R, introduction to Bayesian methods with R and JAGS |
| Dr. Kristian Kleinke | Missing values and multiple imputation, analysis of panel data with missing values, data analysis with R, introduction to R |
| Dr. Rainer Leonhart | Regression analysis, analysis of variance, structural equation modelling, dealing with missing values, explorative multivariate methods |
| Dr. Jana Groß Ophoff | Linear structural equation modelling, item response models; software: Mplus, Conquest, R, SPSS |
| Prof. Dr. Timo von Oertzen | Structural equation modelling with Onyx, optimisation of statistical power in experimental designs |
| Dr. Thomas Schäfer | Research methodology and evaluation (linear structural equation modelling, multilevel analyses, effect sizes and confidence intervals, introduction to SPSS, AMOS, HLM) |
| Prof. Dr. Margrit Schreier | Qualitative content analysis; case selection and generalisation in qualitative research; introduction to qualitative research methods; mixed methods |
| Prof. Dr. Manuel Völkle | Structural equation modelling, analysis of longitudinal data |
| Dr. Till Kaiser | Linear structural equation modelling, analysis of longitudinal data, multilevel analyses, data analysis with Stata/R/SPSS/Mplus |
| Dipl. Psych. Marcel Miché | Data analysis with R (introduction), professional data preparation (in R) of data from an ESM (experience sampling methodology) study, R as a programming language |
| Dr. Andreas Brandmaier | Machine learning methods, structural equation modelling (lavaan, OpenMx, Onyx), change measurement |
| Dr. Annika Wilhelmy | Qualitative research approach of grounded theory, introduction to qualitative research methods |
| Dr. Jan R. Böhnke | Multivariate methods (cross-sectional, longitudinal, multi-level data); item response models; simulation studies (e.g. for statistical power in research designs, validation of results of complex models) Software: R, Mplus, Stata |