Moving from single analysis to multi-team, multiple analyses in research: Editorial

While it is a common practice to conduct single analysis research, Eric-Jan Wagenmakers, Alexandra Sarafoglou, and Balazs Aczel write that subjecting data to multiple analyses by multiple teams creates more robust, meaningful results. Reflecting on the research conducted on the topic of COVID-19 throughout the pandemic, the authors discuss how single analysis practices can blind a researcher to uncertainty and make results seem more precise than they really are. They then provide arguments against the common questions about multi-analysis practices, such as whether journals would baulk at the idea of multi-analyst projects or whether the benefits are outweighed by the costs and effort of such a process. “It is crucial for researchers and society to have an indication of such fragility from the moment the results are published, especially when these results have real-world ramifications,” the authors conclude. “Overall, the benefit of increased insight will outweigh the extra effort.” Nature Note: Archived stories may contain dead links or be missing source links.