Earlier quoted context omitted.
It’s mathematically identical but conceptually different. The things that go into the calculation are different, the numbers that get out of the calculation mean different things. Laughing is healthy though.
You can just shortcut all of that if you're a Bayesian and just plain say "p-values are posterior probabilities under a uniform (improper) prior" and save everyone a lot of time. And if you're doing that, don't care complain that p-values can be misinterpreted, because you're basically just laundering the misinterpretation of p-values. Sure, you are mathematically pure because you made an initial assumption that it c…
I have no interest in laundering the misinterpretation of p-values. I don’t know whose time is saved, frequentists don’t care about the Bayesian interpretation anyway and Bayesians don’t need to restrict themselves to a particular prior. The fact that in some cases you can choose one particular prior to get a numerical value for one probability that is equal to the numerical value for the probability of a completely different thing calculated by someone else doesn’t help anyone much. Bayesians can get the same result on their own if they want.