Dr. Scott Berry applies a statistician’s review of a random trial result published in JAMA – the FAIR-HF2 clinical trial. Interrogating the frequentist paradigm and the focus on the binary outcome of the primary hypothesis test.

Scott Berry convenes co-authors Kert Viele, Joe Marion, and Lindsay Berry to discuss the statistical and developmental nuances of inferentially seamless phase 2/3 clinical trial designs.

In this FACTS webinar, Nick Berry, Senior Statistical Scientist, takes us through how longitudinal models work within the FACTS software.

A Goldilocks trial design is an adaptive clinical trial methodology developed to optimize the sample size dynamically during the course of a trial. Its name references the "just right" principle from the Goldilocks fairy tale—neither too large nor too small. Goldilocks designs seek balance between flexibility and efficiency.

A source of widespread confusion is the entrenched belief that introducing interim analyses “costs” alpha; that is, the assumption that interim adaptations erode the available alpha and require the sponsor to “pay a penalty.” This notion also leads to the myth that just the action of “looking at data” at an interim analysis is bad and costs alpha.

In this solo episode of "In the Interim...", Scott Berry, President and Senior Statistical Scientist at Berry Consultants, addresses deep-rooted confusion in the field of adaptive clinical trial design surrounding the concept of “spending alpha.”