[ianhorn]

> I disagree. Negative results are important. Null results are of very limited interest. The two are worlds apart.

I agree they're different but, but disagree that they're worlds apart. There's a spectrum between them, caused by uncertainty and statistics. If I say the average treatment effect of my new drug is probably somewhere between -x and +y, it could be a negative result or a null result. It's the fuzzy line between statistically insignificant and materially insignificant.

Maybe I only had two patients per experimental cell, so I barely learned anything. The drug's treatment effect on lifespan is between -30 years and +10 years. It's "null" in that we didn't learn much of anything.

Maybe I had a billion patients per cell and I learned that the average treatment effect on lifespan is between -0.001 days and +0.1 days. It's "negative" in that we learned the drug doesn't materially affect lifespan.

The position we seem to be in is that most conventional experiments are powered with a moderate effect size at 80%, meaning that many of our null-or-negative (-x, +y) results will be right around the region where it's unclear whether results are null or negative.