Biostatistics
- Epidemiology, Public Health, Prevention and Survivorship
Prof. Dr. Annette Kopp-Schneider
Head
The Division of Biostatistics‘ mission is to support scientists in performing and publishing excellent reproducible research. We develop efficient experimental designs and devise sound statistical analysis and interpretation of biomedical data. Adequate statistical methods are rarely available ‘off the shelf’ but must be developed and tailored to the specific problem in collaboration with the biomedical researcher. Hence, the Biostatistics group acts as research division with service function.
Our Research
The mission of the Division of Biostatistics is to support DKFZ scientists in performing and publishing excellent reproducible research. Biostatistics is an interdisciplinary science with the aim to provide efficient design of experiments and trials, and devise sound statistical analysis and interpretation of biomedical data. Adequate experimental design and analysis strategies are rarely available ‘off the shelf’ but must be developed and tailored to the specific problem in collaboration with the biomedical researcher. Therefore, the Division of Biostatistics can only provide state-of-the-art support if it actively performs methodological research and implements newly developed analysis strategies. As a consequence, it acts as a research division with a service function.
Our methodological research activities cover a wide range of biostatistical topics, often motivated and interlinked with long-standing collaborations within and outside the DKFZ, including a large number of clinical trials. The close collaboration with biomedical researchers and clinicians allows us to link statistical methodological research and clinical practice, thus contributing to the advancement of translational oncology and precision oncology. Major areas of current research interest include: design and analysis of clinical trials, both in the frequentist setting as well as in the Bayesian framework; identification of prognostic and particularly predictive factors from clinical and molecular data; optimal design and analysis for dose-response relationships, with a focus on combination of substances; measuring dependence between sets of random variables for various data types. We are keen on approaching novel methodological challenges, and indeed, in our collaborations with biomedical scientists, we address a variety of additional research topics. More detailed information about our research activities are given here.