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.

Read the latest news, events, and publications from Metrum Research Group in our Winter 2020 Newsletter.

Here’s what you will find in our newsletter:  

• Join MetrumRG at ASCPT: Our workshop, our Booth and an award!
• New models and blog posts on our website!
• Announcement about our newest team members!
• Upcoming events our scientists will be attending or presenting at.
• Publications and presentations by MetrumRG scientists.

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 fall season brought several opportunities for MetrumRG employees to give to local communities.

MetrumRG scientists traveled to Orlando, FL to join the American Conference on Pharmacometrics for their 2019 annual meeting in October.

Read the latest news, events, and publications from Metrum Research Group in our Fall 2019 Newsletter.

Here’s what you will find in our newsletter:  

• MetrumRG at ACoP10: Our workshops, presentations, and posters!
• Announcement about our newest team members!
• Upcoming events our scientists will be attending or presenting at.
• Publications and presentations by MetrumRG scientists.

The confluence of several factors, including: the growing recognition of the value of quantitative approaches to decision-making in drug development, advancements in numerical methods and analytics, and democratization of modern software engineering, has led to the emergence of multiple pharmacometrics-related software tools, both commercially and publicly licensed. A rigorously managed, high-quality, software development practice is central to reliable and reproducible scientific application and regulatory compliance for these tools. Professional software development best practices should typically be outlined in a Software Development Life Cycle (SDLC) policy or procedure, but the extent of guidance, consistency of methods, adherence to procedures, completeness of quality documentation, and execution rigor vary greatly across software development organizations or teams.