Standard error

In this second instalment of a two-part series, we unpack some of the most commonly used – and most frequently misunderstood – statistical terms in clinical trials and medical research.From p-values and confidence intervals to power, effect sizes, and Type I versus Type II error, we explain what these terms actually mean, how they’re used in practice, and where people often go wrong.

Adaptive clinical trials are often described as “new”, “innovative”, or even “controversial” — but what do they actually mean in practice?In this episode of Standard Error, we unpack the core idea behind adaptive trial designs. Starting from first principles, we explain why adaptive designs emerged, what problems they are trying to solve, and when they genuinely add value over traditional fixed designs.The episode also introduces more advanced ideas — such as seamless designs and response-adaptive randomisation — while being honest about where these approaches help, where they don’t, and why complexity is not always a virtue.This is a practical, concept-driven episode aimed at researchers, clinicians, and students who want to understand adaptive trials without being buried in equations. If you want to understand how modern trials can evolve while they’re running — and why that’s harder than it sounds — this episode is a good place to start.Link to Mike's adaptive trial that was published in The Lancet Psychiatry: https://doi.org/10.1016/S2215-0366(25)00129-4