> The whole NHST edifice starts to seem really shaky once you stop and wonder if "True" and "False" are really the only two possible states of a scientific hypothesis.
The root problem here is that people tend to dichotomise what are fundamentally continuous hypothesis spaces. The correct question is not "is drug A better than drug B?", it's "how much better or worse is drug A compared to drug B?". And this is an error you can do both in Bayesian and frequentist lands, though culturally the Bayesians have a tendency to work directly with the underlying, continuous hypothesis space.
That said, there are sometimes external reasons why you have to dichotomise your hypothesis space. E.g. ethical reasons in medicine, since otherwise you can easily end up concluding that you should give half your patients drug A and the other half drug B, to minimise volatility of outcomes (this situation would occur when you're very uncertain which drug is better).
The root problem here is that people tend to dichotomise what are fundamentally continuous hypothesis spaces. The correct question is not "is drug A better than drug B?", it's "how much better or worse is drug A compared to drug B?". And this is an error you can do both in Bayesian and frequentist lands, though culturally the Bayesians have a tendency to work directly with the underlying, continuous hypothesis space.
That said, there are sometimes external reasons why you have to dichotomise your hypothesis space. E.g. ethical reasons in medicine, since otherwise you can easily end up concluding that you should give half your patients drug A and the other half drug B, to minimise volatility of outcomes (this situation would occur when you're very uncertain which drug is better).