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1. According to Friston & Penny (NeuroImage, 2003) "Posterior Probability Maps and SPMs", on page 1246 they mention a threshold of 0.7% (equivalent to percentage of whole-brain mean signal). So I believe your guess is correct. 2. I am unsure, since the interpretation is different than in frequentist inference. I should think that you can report 0.90 if there is precedent in the literature, or if you can reasonably defend that choice. S Calderbank wrote: > Dear all > > I have conducted some analyses using a conventional frequentist SPM > approach. I want to make some arguments concerning both a presence > and absence of an effect in specific regions. I believe that using a > Bayesian approach (PPM) I can reframe my hypothesis so that I can > identify the probability of finding an effect of a specific size in my > regions - thus allowing me to show evidence in favour of "accepting" > the null hypothesis by showing a low probability of an effect size x. > I have conducted a second level Bayesian estimation on the SPM.mat > arising from the frequentist analysis. My questions are: > > 1. I am a little confused as to whether there have been changes > between SPM2 and SPM5/8 in visualising PPMs. When you choose the > effect size in SPM5 or 8 does the value which appears in the gui (in > my case 0.01) refer to a 1% change in the global mean? From the > previous literature it seems that the conventional way of trying to > demonstrate a null result is to visualise > 1SD of the prior variance > and report the probability at specified regions. How do I find this > value? > > 2. It seems it is common practice to set the probability value to > >.95. Is this still the case even in the instance of a one sided > t-test where one would assume a more conventional criterion would be >.90? > > Any help would be very appreciated. > > Kind regards > > Simon