Hello all,

I have only just gotten my feet wet in Bayesian analysis, but I’ve read parts Kruschke’s textbook, as well as Kaplin’s Bayesian Stats for the Social Sciences. Both books emphasize how picking a prior that is conjugate to the likelihood distribution is ideal. However, for the Logistic Regression I’m currently running, the conjugate prior is the Beta distribution, which I don’t see listed in rstanarm’s priors list.

So my question is, how important is specifying the Beta distribution? How much is it going to affect the analysis in general, and my parameter estimates specifically, if I use (for example) the student t instead?