It has been proposed that preregistration improves the interpretability
and credibility of research findings. This talk presents a critical view
of this proposal, focusing on the proposed benefits of preregistration
vis-à-vis confirmatory and exploratory analyses; HARKing; motivated
reasoning; overfitting; deviations from planned analyses; undisclosed
multiple testing; p-hacking; the garden of forking paths; optional
stopping; test severity; reporting null results; publication bias; and
replication rates. In conclusion, preregistration does not improve the
interpretability and credibility of research findings when other open
science practices are in place, including: (a) rationales for current
hypotheses and analytical approaches; (b) publicly available research
data, materials, and code; and (c) demonstrations of the robustness of
research conclusions to alternative interpretations and analytical
approaches