The difference between the most vs least spooky X-risks is way more than a 100X difference.
I think I would agree with this, if I had to put a number.
What I mean in my comment is, with this model, if you say okay let’s pick a bigger n so that we see bigger differences in OOMs, then you are also introducing more points of failure in the estimation, and that effect dominates.
Do you have an a priori reason to discard this? Besides the conclusion being wacky, which is a good reason to discard a model anyways.
The difference between the most vs least spooky X-risks is way more than a 100X difference.
I think I would agree with this, if I had to put a number.
What I mean in my comment is, with this model, if you say okay let’s pick a bigger n so that we see bigger differences in OOMs, then you are also introducing more points of failure in the estimation, and that effect dominates.
Do you have an a priori reason to discard this? Besides the conclusion being wacky, which is a good reason to discard a model anyways.
I agree that merely increasing n would not change the OP’s conclusion that errors dominate.
My point is more that they picked too big of parameters for error variance and too small of parameters for risk-size variance.