Statistical Modeling of Primary Data Unit
The unit "Statistical Modeling of Primary Data" is the contact for all questions related to the statistical-methodological aspects of planning, conducting, evaluating and publishing epidemiological studies. The aim is the biometrically sound conception of projects, the adaptation or development of suitable analytical methods, and the statistical training of staff. This applies both to BIPS-internal research projects and to studies that are located outside BIPS and conducted together with the unit. In addition, the so-called federated data analysis is gaining in importance, in which analysis codes are transmitted to the data while maintaining data protection and data security and no personal data need to be transferred on the part of the data-holding organizations.
However, the unit does not see its actual task in the routine preparation of standard analyses, but explicitly in the adaptation and further development of innovative analysis procedures. For example, together with three other European study centers, approaches are being developed to improve the classification of objectively measured exercise and eating behavior with the help of machine learning methods. In another project, artificial intelligence methods are also being used to derive optimal diagnostic parameters (so-called biomarkers) by enriching cancer registry data with diagnostic data from pathology, which could then form the basis for more effective treatment methods. Improving data quality is also the goal of a DFG-funded project in which tools are being developed to assess the data quality of epidemiological studies as standardized as possible. It is also intended to help strengthen the basis for the FAIR criteria of findability, accessibility, interoperability and reusability. In this way, the project ties in seamlessly with the goals of NFDI4Health, an interdisciplinary research consortium in which the unit is also involved. One of the aims of this initiative is to develop a centralized catalog of health research-relevant study data with user-friendly data access management and to improve the linking of research-relevant data sources in Germany, taking into account the special data protection requirements of personal health data. In this context, the unit is developing an interactive online evaluation tool for the analysis of existing primary data and software for the use of generalized additive models for location, scale and shape parameters (GAMLSS), taking into account the problem of distributed data.
Current Projects
Only currently running projects or those where publications are still in preparation or those that ended less than a year ago will be shown. The entries are sorted alphabetically.
- Cross-departmental Center B: Data Science
- Adaption effectiveness study of the Healthy Dads, Healthy Kids programme in Germany
- Cross-departmental Center A: Research Data Infrastructure
- Determinants of eating behaviour in European children, adolescents and their parents
- Development and evaluation of three-stage procedures for modeling exposure patterns in epidemiological studies
- Effects of bariatric procedures
- Growing up healthy: Obesity prevention tailored to critical transition periods in the early life-course
- Identification and prevention of dietary- and lifestyle-induced health effects in children and infants
- Monitoring of physical activity and promotion of physical activity - development of indicators for the prevention indicator system of the federal states
- National research data infrastructure for personal health data
- NFDI4Health - Task Force COVID-19: Better understanding the COVID-19 outbreak and its consequences through integrated and harmonised research efforts
- Pooled analysis of European case-control studies on the interaction of occupational carcinogens in the development of lung cancer
- Record linkage of cancer registry data and multimodal, reporting-based diagnostic data for Al-based biomarker detection
- Wearable sensors for the assessment of physical and eating behaviours
Staff
Buck, Christoph, Dr.
Tel.: +49 (0)421 218-56944
Fax: +49 (0)421 218-56941
buck(at)leibniz-bips.de
Intemann, Timm, Dr.
Tel.: +49 (0)421 218-56984
Fax: +49 (0)421 218-56921
intemann(at)leibniz-bips.de
Mändle, Andreas, Dr.
Tel.: +49 (0)421 218-56794
maendle(at)leibniz-bips.de
Peters, Manuela, Dr.
Tel.: +49 (0)421 218-56924
Fax: +49 (0)421 218-56941
mpeters(at)leibniz-bips.de
Pohlabeln, Hermann, Dr.
Tel.: +49 (0)421 218-56947
Fax: +49 (0)421 218-56941
pohlabeln(at)leibniz-bips.de
Swenne, Annika
Tel.: +49 (0)421 218-56943
Fax: +49 (0)421 218-56941
swenne(at)leibniz-bips.de
Hermann Pohlabeln
Head of Unit
Contact:
Dr. Hermann Pohlabeln
Tel: +49 (0)421 218-56947
Fax: +49 (0)421 218-56941
More units and research groups
- Statistical Modeling of Primary Data
- Statistical Modeling of Secondary and Registry Data
- Statistical Methods for Genetics and Molecular Epidemiology
- IT, Data Management and Medical Documentation
- Statistical Methods for Causal Inference Research Group
- Emmy Noether Junior Research Group: Beyond Prediction - Statistical Inference with Machine Learning