«Statisticians are second-class mathematicians, third-rate scientists and fourth-rate thinkers. They are the hyenas, jackals and vultures of the scientific ecology: picking over the bones and carcasses of the game that the big cats, the biologists, the physicists and the chemists, have brought down.»

- Stephen Senn, in: Dicing with Death (2003)

I was on the trajectory of becoming a big cat but then fully embraced the life of a hyena. I am a research fellow at the Institute of Mathematics of the University of Zurich in the Applied Statistics group of Professor Reinhard Furrer. There, I try to develop a consistent framework for good statistical practice in exploratory animal research in order to improve the reproducibility of animal studies.

Research focus

I work at the interface of applied statistics and biomedical research, with a special focus on the statistical design and analysis of exploratory research. Beyond that, I am interested in the prerequisites that need to be fulfilled for scientific knowledge to be reliable and in the societal and political role that scientific knowledge plays.

PhD thesis

Experimental design and analysis necessitates the combination of scientific and mathematical models in a consistent fashion. Every experiment usually begins with a hypothesis about the world, stated in quite general terms and of broad scope: the Primary Model. To inquire about the hypothesis scientifically, it has to be transformed into a hypothesis which is empirically testable with current methods and resources: the Experimental Model. Hence, a suitable experimental context with clearly defined parameters and outcomes must be specified. Both levels are usually stated in the scientific language of the discipline in which the experiment takes place and only the next two levels are in the realm of statistics. First, the data generation process must be described by a Data Generation Model, followed by the specification of the experimental process in the form of the Experimental Design Model which is then combined with a particular Data Analysis Model for analysis. that specifies the statistical measures and tests that are used to analyze the data.

The goal of my PhD thesis is to provide a consistent hierarchical framework relating the inferential paths from a Primary Model about the world to the data gathered and back to the Primary Model in exploratory experiments. The value of such a framework consists in helping expose and prevent logical and mathematical inferential challenges and also aid the consistent and meaningful planning of experiments, which is demonstrated in three use cases.

Selected Publications

«The presumption that all we need is an agreement on numbers - never mind if they’re measuring different things - leads to pandemonium.»

- Deborah Mayo, in: Statistical Inference as Severe Testing (2018), xi

  • Servan Grüninger (2023). Stefano Franscini: The statistician who built a nation, Significance, Volume 20, Issue 4, August 2023, Pages 40–43, https://doi.org/10.1093/jrssig/qmad066.

  • Reja Wyss, Silvia Maier, Odile Ammann, Servan L. Grüninger, Darius Farman. 2023. Wer wird gehört? Wissenschafter:innen in den Anhörungen der parlamentarischen Sachbereichskommissionen. Swiss Academies Communications. Vol 18. Nr. 3.

  • Natascha Drude, Lorena Martinez-Gamboa, Meggie Danziger, Anja Collazo, Silke Kniffert, Janine Wiebach, Gustav Nilsonne, Samuel Pawel, Florian Frommlet, Leonhard Held, Daniel Segelcke, Bernhard Voelkl, Tim Friede, Astrid Dempfle, Edgar Brunner, Marie Juliane Jung, Esther Pogatzki-Zahn, Lars Björn Riecken, Georg Kuhn, Matthias Tenbusch, Lina Maria Serna Higuita, Frank Konietschke, Edmond J. Remarque, Charlotte Micheloud, Sophie Piper, Bernhard Haller, Servan Grüninger, Katrin Manske, Sebastian Kobold, Marion Rivalan, Lisa Wedekind, Juliane Wilcke, Anne-Laure Boulesteix, Marcus Meinhardt, Rainer Spanagel, Simone Hettmer, Irene von Lüttichau, Carla Regina, Ulrich Dirnagl, Ulf Toelch. 2022. Planning preclinical confirmatory multicenter trials to strengthen translation from basic to clinical research. transl med commun 7, 24. https://doi.org/10.1186/s41231-022-00130-8.

Click on the publication title to see the articles. For a full list, see here. For popular science and non-scientific articles, see here.

Lectures

Talks

Click on the title of the talks to see the slides. For a complete list of talks and presentations, see here.

Resources

Resources that might be useful to you if you are working in the area of animal research, study design or reproducibility and good statistical practice

  • Guidance document for animal researchers (preliminary version - currently being overhauled): What to consider when planning and describing your study in a licence application for animal experiments. IMPORTANT NOTE: This is a living document and will be extended and adapted if deemed necessary. Also, note that it is geared towards the licence application process in the canton of Zurich but that it is not an official document issued or endorsed by the cantonal authorities or the Animal Research Commission of the Canton of Zurich.

Repositories

You can find my Github repositories here. Note that I am currently in the process of merging the different Github I created over the years, thereby overhauling the repositories worth keeping and clearing out others. As of now, only my current Master thesis project and a small pet project is visible, other repositories will become visible over time. In the meantime, share my delight for this CV I just created using pagedown!

Commission Work

I am a member of the Animal Research Commission of the Canton of Zurich: The commission assesses the scientific and ethical validity of animal research proposals of all animal experiments conducted in the canton of Zurich, predominantly from ETH Zürich and the University of Zurich. In my commission work, I put special emphasis on experimental design and good statistical practice along the lines that are outlined in this guidance document here. Due to the confidentiality rules that apply, I can in general not publicly comment on issues regarding individual applications. For more details, see this text here (in German).

Reviews

I reviewed scientific papers for the following journals, primarily focusing on questions of animal research and biostatistics:

  • Laboratory Animals, Preclinical pilot studies: five common pitfalls and how to avoid them, February 2024

  • Laboratory Animals, Preclinical pilot studies: five common pitfalls and how to avoid them, December 2023

  • Springer Nature Scientific Reports, Over 110 Million Mice and Rats Are Bred and Used in United States Laboratories, November 2020

  • Springer Nature Scientific Reports, Over 110 Million Mice and Rats Are Bred and Used in United States Laboratories, October 2020

  • Springer Nature Scientific Reports, The “Completely Randomised” and the “Randomised Block” Are the Only Common Experimental Designs Which Can Avoid Bias and Irreproducibility in Pre-clinical Research, July 2020

  • Springer Nature Scientific Reports, The “Completely Randomised” and the “Randomised Block” Are the Only Common Experimental Designs Which Can Avoid Bias and Irreproducibility in Pre-clinical Research, March 2020

Boasting section

In Switzerland, showcasing your achievements too openly is usually regarded as rather impolite. It’s OK to take pride in personal achievements but please don’t rub it under people’s nose! That means that I’m a bit in a pickle as the academic system demands the exact opposite behaviour, namely: Look, fellow scientists, I received this scholarship, got that grant and won those prizes - can I get tenure now?

So, as a compromise, I provide you with some successful (yay!) and unsuccessful (nay!) attempts at competing in the scientific game for funds and fame: