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Clinical Trial Design

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

12
Mar
5 min read

What Randomization Can't Fix

The last post argued that how you randomize is a design decision most biostatisticians treat as settled before the interesting work begins. REMAP-CAP showed what happens when that decision is taken seriously. The carat package showed that even standard covariate-adaptive randomization has inferential consequences most of us aren't