I see that the default priors for logistic regression coefficients in brms is a student t with 3 degrees of freedom and a scale parameter of 10.
According to the Stan developers “Prior Choice Recommendations” Github page, the scale parameter for this prior is suggested to be between 3 and 7. I wonder why a scale parameter of 10 was chosen as the default?
I’m asking this question in part because I recently worked through chapter 11 of Statistical Rethinking (2nd Ed) in which McElreath suggests that something such as a normal(0, 1.5) prior will result in a fairly flat prior on the probability scale (see figure 11.3). Assuming I’m doing the prior predictions correctly, his student t prior set by brms still puts a lot of the density near both 0 and 1, which is making me dive into best practices for weakly informative priors in these kinds of models.
Any insight would be greatly appreciated!