I am modelling a logistic binomial response with around 10 (continuous and categorical) explanatory variables. I would like to model it as a bayesian glm and had a look at the bayesglm function on ARM (package).
The package says: modeling with independent normal, t, or Cauchy prior distribution for the coefficients.
So since I have both categorical and continuous independent variables followed by a binary response variable, would a cauchy or normal distribution be best suitable (I had previously thought a beta would be best since my response variable was binomial)?
A bit lost on what prior scale and prior df to use from the package. Can I please get some help and advice on what distribution (and values) I should use.
Can I also ask, are there any other ways I can compute a bayesian model to make predictions? thank you