Hypothesis tests and estimations are sometimes criticised because their results generally depend on the probability functions over the entire sample space, and not exclusively on the probabilities of the observed sample. That is, the decision to accept or reject the null hypothesis depends not just on the probability of what has actually been observed according to the various hypotheses, but also on the probability assignments over events that could have been observed but were not. A well-known illustration of this problem concerns so-called optional stopping (Robbins 1952, Roberts 1967, Kadane et al 1996, Mayo 1996, Howson and Urbach 2006).