Heh. Fair enough, John, I suppose that someone has to arbitrage the books. I’ll add it to Jane Galt’s observation regarding the genuine usefulness of salad forks.
I agree that 0.005 is equally pulled out of a hat. But I also agree on your earlier observation regarding there being some necessity for standardization here.
Personally, I would prefer to standardize “small”, “medium”, and “large” effect sizes, then report likelihood ratios over the point null hypothesis. A very strong advantage of this approach is that it lets someone do a large study and report a startling likelihood advantage of 1000 for “no effect” over “small effect”, rather than just the boring old phrase “not statistically significant”. This is probably worth its own post, but I may not get around to writing it.
Heh. Fair enough, John, I suppose that someone has to arbitrage the books. I’ll add it to Jane Galt’s observation regarding the genuine usefulness of salad forks.
I agree that 0.005 is equally pulled out of a hat. But I also agree on your earlier observation regarding there being some necessity for standardization here.
Personally, I would prefer to standardize “small”, “medium”, and “large” effect sizes, then report likelihood ratios over the point null hypothesis. A very strong advantage of this approach is that it lets someone do a large study and report a startling likelihood advantage of 1000 for “no effect” over “small effect”, rather than just the boring old phrase “not statistically significant”. This is probably worth its own post, but I may not get around to writing it.