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In my first post in this series, I proposed a “starter kit” for developing a statistical argument. This “starter kit” included considerations related to both the direction of effects (“[Is] the association directionally consistent with known mechanistic accounts (e.g. based on enzymology)?”) and the magnitude of effects (“Does the association have a magnitude that is consequential in some practical sense?”). In this post, I argue that “significance language” can play a valuable role in discussing the estimated direction of effects, even if supplementary approaches are needed to address more complex questions about magnitude.

This is the first in a series of blog posts that will focus on practical problems of summarizing statistical evidence in the context of biomedical science, using the 2016 ASA statement on p-values and significance as a guide. I hope and expect that these posts will find a readership that does not entirely agree with my views in all of their particulars, and that this readership takes advantage of the blog / combox format to register both their agreements and disagreements. Merely good ideas are insufficient to the task at hand ; a shared understanding has to develop in the community of practice ; my hope here is to provide a forum for discussion for that community.