Epidemiology and Biometry (» Postal address)
- Expectile and Quantile Regression
- Semiparametric Regression
- Longitudinal Data and Mixed Models
- Time to Event Analyses
- Instrumental Variables
- Graphical Models
- 01/2018: Certificate for university level teaching from the University Oldenburg
- since 10/2014: Postdoctoral Researcher (until 02/18 Akademischer Rat) in the Division for Epidemiology and Biometry at the Department of Health Services Research of the University Oldenburg
- 2012 - 2014: Akademischer Rat at the Chair for Statistics at the Department of Economics of the University Göttingen
- 03/2012: Dissertation with the topic "Semiparametric Expectile Regression" at the University Oldenburg
- 2009 - 2012: PhD student and scientific assistant at the Institute for Mathematics at the University Oldenburg
- 04/2009: Diploma thesis in mathematics with the topic "Validation of undirected graphical models" at BIPS / University of Bremen
- 2003 - 2009: Studies of mathematics at the Universities of Kaiserslautern und Bremen
- Project for the German Research Foundation (DFG) "Verteilungsregression für Ereigniszeiten" / "Distributional regression for times to event" (together with Verena Jürgens and Antje Timmer)
- Project for the German Research Foundation (DFG) "Strukturiert Additive Verteilungsregression" / "Structured additive distributional regression" (together with Thomas Kneib)
- DAAD travel grant for an invited presentation at the CMStatistics 2015 in London
- Roeper J, Falk M, Chalaris-Rissmann A, Lueers A, Wedeken K, Stropiep U, Tiemann M, Heukamp L, Otto-Sobotka F, Griesinger F. TP53 co-mutations in EGFR mutated patients in NSCLC stage IV: A strong predictive factor of ORR, PFS and OS in EGFR mt+ NSCLC. Oncotarget (accepted)
You can find a list of further publications and presentations at Publications.
Current lectures and seminars can be viewed here.
The current lectures target first year master students who want to use inductive statistics in their further studies or theses. The lectures contain basic statistic analysis methods and their applications with the software R.
Foundations of STS: Statistics and Programming (VL)