Biometry
The institute has been in the position to assemble biometricians experienced in a wide range of epidemiological studies (case control, cohort, cross-sectional, longitudinal, incidence studies, etc.) as permanent staff. For specific research projects, a number of short-term employees as well as postgraduate students (usually financed by third parties) extend the range of methods employed in the department. In this context the department also offers the opportunity to write a PhD thesis.
Methods development
We are presently working on diverse topics: these include statistical issues related to the pharmacoepidemiologic research database (twophase studies, control for confounding - Statistical Modeling of Secondary and Registry Data Unit), improvement of statistical procedures in the analysis of gene-gene- and gene-environment interactions, the identification of biological pathways involved in the development of diseases and in the statistical modeling of pathways, accumulations of risk or critical time periods in life-course epidemiology, statistical modeling of nutrition data and use of geographical information systems in epidemiologic studies (Statistical Modeling of Primary Data Unit). Furthermore, the department engages in the development of methods for causal inference, e.g. for instrumental variables or time-varying confounding (Statistical Methods for Causal Inference Research Group), and statistical machine learning (Emmy Noether Junior Research Group: Beyond Prediction - Statistical Inference). With the improved accessibility of research data, development of methods for analysis and combining data, for example by means of record linkage or distributed analyses, is increasingly important.
Statistical support - quantitative methods consulting service
The department also houses a methods consultancy service that is used BIPS-internally as well as externally by other research institutions and scientifically working clinicians, primarily from Bremen and the surrounding region. Support is mainly requested in the planning phase of studies e.g. on the selection of the study design or on sample size calculations. Appropriate analysis methods are proposed and/or developed and support in the application of methods as well as in the interpretation and presentation of results is provided.
Within the inter-departmental working group GeTTCausal (GePaRD & Target Trials for Causal Inference), we combine expertise in secondary data analysis, causal inference, and clinical epidemiology to best analyze important causal questions based on GePaRD using the "target trial emulation" (TTE) approach.
Staff
Bergen, Luca
Tel.: +49 (0)421 218-56796
bergen(at)leibniz-bips.de
Börnhorst, Claudia, Dr.
Tel.: +49 (0)421 218-56946
Fax: +49 (0)421 218-56941
boern(at)leibniz-bips.de
Braitmaier, Malte, Dr.
Tel.: +49 (0)421 218-56983
Fax: +49 (0)421 218-56941
braitmaier(at)leibniz-bips.de
Buck, Christoph, Dr.
Tel.: +49 (0)421 218-56944
Fax: +49 (0)421 218-56941
buck(at)leibniz-bips.de
Burk, Lukas
Tel.: +49 (0)421 218-56955
Fax: +49 (0)421 218-56941
burk(at)leibniz-bips.de
Didelez, Vanessa, Prof. Dr.
Tel.: +49 (0)421 218-56939
Fax: +49 (0)421 218-56941
didelez(at)leibniz-bips.de
Foraita, Ronja, Dr.
Tel.: +49 (0)421 218-56954
Fax: +49 (0)421 218-56941
foraita(at)leibniz-bips.de
Frielinghaus, Maria
Tel.: +49 (0)421 218-56791
Frielinghaus(at)leibniz-bips.de
Gabbert, Anja
Tel.: +49 (0)421 218-56934
Fax: +49 (0)421 218-56941
gabbert(at)leibniz-bips.de
Gesing, Nils Fabian
Tel.: +49 (0)421 218-56935
Fax: +49 (0)421 218-56941
gesing(at)leibniz-bips.de
Golchian, Pegah
Tel.: +49 (0)421 218-56790
golchian(at)leibniz-bips.de
Herbinger, Julia, Dr.
herbinger(at)leibniz-bips.de
Kapar, Jan
Tel.: +49 (0)421 218-56929
Fax: +49 (0)421 218-56941
kapar(at)leibniz-bips.de
Koenen, Niklas
Tel.: +49 (0)421 218-56933
Fax: +49 (0)421 218-5641
koenen(at)leibniz-bips.de
Kollhorst, Bianca, Dr.
Tel.: +49 (0)421 218-56980
Fax: +49 (0)421 218-56941
kollhorst(at)leibniz-bips.de
Langbein, Sophie
Tel.: +49 (0)421 218-56886
langbein(at)leibniz-bips.de
Ludewig, Alina
Tel.: +49 (0)421 218-56882
Fax: +49 (0)421 218-56941
ludewig(at)leibniz-bips.de
Niemeyer, Marieke
Tel.: +49 (0)421 218-56876
Fax: +49 (0)421 218-56941
niemeyer(at)leibniz-bips.de
Pohlabeln, Hermann, Dr.
Tel.: +49 (0)421 218-56947
Fax: +49 (0)421 218-56941
pohlabeln(at)leibniz-bips.de
Runge, Lea
Tel.: +49 (0)421 218-56979
runge(at)leibniz-bips.de
Schaffer, Inga
Tel.: +49 (0)421 218-56871
Fax: +49 (0)421 218-56941
schaffer(at)leibniz-bips.de
Viebrock, Jost
Tel.: +49 (0)421 218-56951
Fax: +49 (0)421 218-56941
viebrock(at)leibniz-bips.de
Volkmar, Philipp Alexander
Tel.: +49 (0)421 218-56948
Fax: +49 (0)421 218-56941
volkmar(at)leibniz-bips.de
Wright, Marvin N., Prof. Dr.
Tel.: +49 (0)421 218-56945
Fax: +49 (0)421 218-56941
wright(at)leibniz-bips.de
Departmental News
Lifespan AI - successful kick-off meeting
- Created by Rasmus Cloes
- Research Data Infrastructures and Data ScienceStatistical Methods in EpidemiologyNews
The Lifespan AI project began its work back in June. Now all those involved were able to exchange ideas for the first time at a joint meeting.
In Lifespan AI, sensitive data is used in compliance with ethical and data protection regulations to advance machine learning (ML) and deep learning (DL) models. The aim is to gain causal insights in order to uncover the causes of complex diseases and optimize prevention strategies. Last Thursday, all those involved in the project were able to exchange ideas for the first time and agree on the common goals.
Lifespan AI - these are the goals
The Lifespan AI work program consists of six projects grouped into three themes that pursue the Lifespan AI vision from different perspectives: Data and Methods (D), Models and Interpretation (M), and Inference and Causality (C). D1 will advance DL strategies to explore and process long-term temporal changes based on the integration of high-dimensional data from multiple sources; D2 will combine neural networks and mixed-effects models to predict individual health trajectories over the life course; M1 will develop "normalizing flow" methods to infer joint distributions and conditional densities for health data; M2 will create a cognitive digital twin from everyday human activities to predict change across age groups; C1 will develop time-adaptive, explainable AI methods for recurrent neural networks and event times; and C2 will derive a framework for causal discovery in longitudinal studies, combining different datasets and accounting for non-linearities.
Further information on the project can be found here.
![[Translate to Englisch:] Das Team von Lifespan AI.](/fileadmin/_processed_/7/5/csm_lifespan_AI_Gruppe_rc_bd2b3aec4b.jpg)
Marvin N. Wright
Head of Department
Contact:
Prof. Dr. Marvin N. Wright
Tel: +49 (0)421 218-56945
Fax: +49 (0)421 218-56941
Vanessa Didelez
Deputy Head of Department
(Head of Research Group)
Contact:
Prof. Dr. Vanessa Didelez
Tel: +49 (0)421 218-56939
Fax: +49 (0)421 218-56941