Evidence in the Wild

Evidence in the Wild

Because the real world didn’t read your protocol

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Latest Articles

26
Mar
6 min read

When the AI Statistician Gets It Right (and Why That's the Dangerous Part)

A few months ago, I asked an LLM to design my clinical trial. It recommended a Bayesian borrowing design for a Phase 2 single-arm oncology trial. The response was fluent, well-organized, and cited the right methods. It was also wrong—in ways that would survive a casual review. That post

24
Mar
7 min read

When Response-Adaptive Randomization Is the Right Design: Lessons from PAIN-CONTRoLS

A four-arm neuropathy trial shows what RAR looks like when it's used for the right reasons

17
Mar
13 min read

Bayes through the Looking-Glass: Assessing the Credibility of Clinical Trial Outcomes by Inverting Bayes’s Theorem

A trial reports p = 0.03. As this is less than 0.05, it meets the well-known criterion for being statistically significant. But is the trial outcome also credible? That depends on what you mean by credible—and on information the p-value alone cannot provide. Statistical significance tells you the