BF for planned comparisons in multi-factor designs
I do have some questions regarding comparisons in multi-factor designs:
I generally understand how to compute posterior odds using the posterior() function, but I am at a loss about how to compute prior odds in these cases.
For example, if I have a 2-by-2 design, and my restricted model is that one simple effect is larger than the other simple effect, are the prior odds 0.5 because in the unrestricted model, either simple effect can be larger than the other?
What about if (in the same design), my restricted model is that there are two simple effects, and that one of them is larger than the other? I have no idea how to compute the prior odds in this case...
(Also, which BF would I have to divide by to get the restricted vs. null BF in each of these cases?)
Similarly, when computing a BF for a restricted correlation, I understand that if my restricted model is that r>0, my prior odds are 0.5, but what if my restricted model is that r>0.3?
I have some more queries along these lines, but I'll take it one step at a time