Over the course of the last decade, a variety of methods have been proposed for fitting pharmacometric models to outcomes with constrained pharmacodynamic scales. One approach is to model the residual distribution as a Beta distribution (methods that employ this strategy are referred to broadly as "Beta regression" methods.) There are several reasons why one might choose to NOT use Beta regression in pharmacometrics:
Topics: Open Science
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.
In my previous post, I proposed a “starter kit” for developing a statistical argument. An essential ingredient in this “starter kit” was the identification of the context of inquiry as being confirmatory, explanatory, or something in between. In this post, I propose several criteria for defining a confirmatory context, and I suggest principles for using the language of “statistical significance” when confirmatory contexts do not obtain.
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.
The peace of another typically idyllic summer afternoon in The Happy Valley was ruptured as one Ahmed Elmokadem strode confidently onto the hallowed soccer pitch of Curtis Field E. Fans immediately sensed that this would not be business as usual as Elmokadem jarringly threw down, boldly selecting a team consisting of only interns and himself. Accounts differ, but some say there were half-muffled laughs of derision at this choice. No dispositive documentation of this has been found to date. Said team was soon to become known as the "Young Punks", for reasons that should be self-evident. Yin to the Yang, team "Old School" materialized in opposition. Fans remarked in hushed tones how the geriatric name of this team belied the preternatural handsomeness and athleticism of its members.
“Prevention … we have never uttered that word at the Alzheimer’s Association International Conference, and here we actually highlighted three clinical trials in the planning for prevention of Alzheimer’s … “. This comment from Dr. Mario Carrillo gives voice to the enthusiasm and interest of the attendees at the standing-room-only Alzheimer’s Association International Conference session entitled, “Collaboration for Alzheimer’s Prevention: Common Issues Across Presymptomatic Treatment Trials”, in which the A4, API, and DIAN prevention trials were discussed.
Topics: Neurodegenerative Diseases