Biostatistics Department

The Department of Biostatistics is a key center for the development and application of statistical methods in health research. It supports epidemiological and clinical studies with precise, innovative statistical approaches. Experts in the department develop methods to analyze complex datasets, helping to draw reliable conclusions about health risks, disease causes, and the impact of interventions.

One of our main foci is on methodological development for analyzing longitudinal and big data studies, which are essential for understanding trends and changes in population health. These methods play a crucial role in investigating both chronic and acute diseases, as well as their prevention. Furthermore, the Department is the major contributor to the UZH Master Program in Biostatistics and the Center for Reproducible Science (CRS).

Head of Department: L. Held

The correct design and later analysis of biomedical research studies is at the center of our interest, specifically for epidemiological and clinical applications, as well as in general replication studies. We develop and validate new methodological approaches for statistical aspects of reproducibility and replicability, Bayesian inference and infectious disease epidemiology.

Biostatistics
Credibility of Biostatistical Methods
Evidence-based Drug Development

Our contributions follow the "think once, apply everywhere" principle. We are interested in the excavation of statistical core principles allowing us to understand a 
broad class of models under a unifying theoretical umbrella. Connections between superficially unconnected models or problems become visible, construction principles for addressing open issues can be derived, and computational issues affecting many estimation and inference procedures alike can be identified and, possibly, solved. 

Models and Computing

Our Division focuses on the translation between clinical and methodological research. Across different clinical disciplines, we focus on study design, statistical programming, statistical analysis, and interpretation of results while adhering to highest standards regarding reproducibility.

Clinical Research Methods

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Evelyne Bielser (E-Mail)