This digital event discusses the pros and cons of preregistration. Preregistration allows researchers to put their method and planned analysis on record before data are being collected. Preregistration clearly guards against a number of potentially questionable practices such as p-hacking and HARKing. But there is more to this than first meets the eye, and those nuances are explored in this digital event.

• Stephan Lewandowsky kicked off the discussion by outlining the basic idea behind preregistration.
• Stephen Lindsay then outlined the many good reasons why we should all preregister our method and analyses. A must-read for anyone new to this issue.
• Klaus Oberauer pointed out that while preregistration of an analysis plan avoids outcome-driven choices during analysis, the preregistered plan is as arbitrary as any other. So why should it be privileged?
• Richard Morey recognizes the importance of preregistration to increase transparency and methodological rigour, but worried that if it becomes ritualized it may suppress the skepticism that we should bring to our data.
• Danielle Navarro proposed that in the rigorous realm of computational modeling, there are other tools that can achieve even more transparency than preregistration, such as open notebooks and public version control systems.
• Iris van Rooij amplified the need for better theory development in psychology, noting that we need not more phenomena but better explanations.
• Richard Shiffrin argued against preregistration on the grounds that science is too complex to permit being guided by simple rules.
• Stephan Lewandowsky made the point that preregistration is part of a necessary shift in scientific culture, but that new practices deserve to be examined in depth and that their nuances must be explored.