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Selected Publications

Amrhein, Valentin, Greenland, Sander, McShane, Blake (2019) Retire statistical significance. Nature 567:305–307. https://doi.org/10.1038/d41586-019-00857-9

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Amrhein, Valentin, Trafimow, David, Greenland, Sander (2019) Inferential statistics as descriptive statistics: there is no replication crisis if we don’t expect replication. The American Statistician 73:262–270. https://doi.org/10.1080/00031305.2018.1543137

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Amrhein, Valentin, Korner-Nievergelt, Fränzi, Roth, Tobias (2017) The earth is flat (p < 0.05): significance thresholds and the crisis of unreplicable research. PeerJ 5:e3544. https://doi.org/10.7717/peerj.3544

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Roth, Tobias, Plattner, Matthias, Amrhein, Valentin (2014) Plants, birds and butterflies : short-term responses of species communities to climate warming vary by taxon and with altitude. PLoS ONE 9:e82490. https://doi.org/10.1371/journal.pone.0082490

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Amrhein, V, Korner, P, Naguib, M (2002) Nocturnal and diurnal singing activity in the nightingale : correlations with mating status and breeding cycle. Animal Behaviour 64:939–944. https://doi.org/10.1006/anbe.2002.1974

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Selected Projects & Collaborations

Petite Camargue Alsacienne

Research Project | 1 Project Members

For many years, the main focus of our research was on song, behaviour and migration of Nightingales (Luscinia megarhynchos) in the nature reserve Petite Camargue Alsacienne just north of Basel, where students can live and work at the research station. More recently, we started investigating the effects of natural grazing by Konik horses and Highland cattle. Other current projects involve different species of songbirds in the Swiss National Park, in the Val Piora (Ticino) and on the Furka Pass. We are also contributing to analyzing large ecological data sets from monitoring programs such as the Biodiversity Monitoring Switzerland. Often, our students work on projects offered by our colleagues at the Swiss Ornithological Institute (Vogelwarte Sempach) or at the environmental consulting company Hintermann & Weber AG. An integral part of our research, and of science in general, is thinking about statistical inference, communication, and reproducibility. For more information, please visit https://camargue.unibas.ch/en

Basel Reproducibility Network

Research Networks of the University of Basel | 10 Project Members

Das Basel Reproducibility Network hat sich zum Ziel gesetzt, offene, transparente und reproduzierbare akademische Forschung in allen Disziplinen der Universität Basel zu fördern. Das interdisziplinäre Netzwerk bringt Forschende aus verschiedenen Fakultäten zusammen, um Best Practices in den Bereichen Forschungsmethodik, statistische Analyse, offene Daten und wissenschaftliche Kommunikation zu fördern. Das Netzwerk organisiert Weiterbildungsaktivitäten, Seminare und Workshops zu Schlüsselthemen der Reproduzierbarkeit, wie z.B. robuste statistische Methoden, Vorregistrierung von Studien, Open-Source-Entwicklung und verantwortungsvoller Datenaustausch.

Durch die Vernetzung von Forschenden, die an der Optimierung der Zuverlässigkeit von Forschungsresultaten interessiert sind, bietet das Netzwerk eine Plattform für die Entwicklung innovativer Projekte, die gemeinsame Nutzung von Ressourcen und die Umsetzung von Strategien zur Verbesserung der Qualität und Wirkung von Forschungsergebnissen. Das Basel Reproducibility Network arbeitet mit nationalen und internationalen Initiativen zusammen und trägt so zu den Bestrebungen der gesamten wissenschaftlichen Community bei, die Herausforderungen der Reproduzierbarkeit in der Forschung anzugehen.

Am Forschungsnetzwerk sind Forschende der medizinischen, naturwissenschaftlichen, psychologischen und wirtschaftswissenschaftlichen Fakultäten der Universität Basel beteiligt.

The Basel Reproducibility Network aims to foster open, transparent, and reproducible academic research across all disciplines at the University of Basel. This interdisciplinary network brings together researchers from various faculties to promote best practices in research methodology, statistical analysis, open data, and scientific communication. The network organizes educational activities, seminars, and workshops to address key issues in reproducibility, such as robust statistical methods, preregistration of studies, open-source development, and responsible data sharing.

By connecting researchers interested in improving research reliability, the network provides a platform for developing innovative projects, sharing resources, and implementing strategies to enhance the quality and impact of research outputs. The Basel Reproducibility Network collaborates with national and international initiatives, contributing to the broader scientific community's efforts to address the challenges of research reproducibility.

Researchers from the Faculties of Medicine, Science, Psychology and Business and Economics at the University of Basel are involved in the research network.