Another question I should have asked is: if one has to account for the prior odds to each model P(M) because they’re not a priori the same, I’m not sure I understand what this corresponds to. It seems we’re talking about the odds of a model integrating out the parameters and the data? Would you happen to know of an example in which the Bayes factor needs to be updated by the model likelihood?