Stephen Senn discusses the evolution of statistical analysis from a design-driven to a more pragmatic approach, highlighting the tension between randomization inference and model-based inference. This document emphasizes the importance of resolving the dichotomy between these approaches, particularly in medical trials, and critiques the limitations of both methodologies. Senn argues for a framework that accommodates the strengths of both randomization and modeling to improve statistical inference. - Download as a PPTX, PDF or view online for free

Background The problem of missing studies in meta-analysis has received much attention. Less attention has been paid to the more serious problem of double counting of evidence. Methods Various problem...

Several times recently, in published papers and in papers I have been asked to review, I have come across the quite incorrect claim that the eligibility criteria of a clinical trial define the target ...

When I was one-and-twenty        I heard a wise man say, “Give crowns and pounds and guineas        But not your heart away; Give pearls away and rubies        But keep your fancy free.” But I was one...

AI, data centres, job losses, globalization. What happens when AI tries to ruin your life? Even if you don t work in tech, this story pulls you in with its vivid world-building and well-rounded charac...