Standard methods for analyzing binomial regression data rely on asympt
otic inferences. Bayesian methods can be performed using simple comput
ations, and they apply for any sample size. We provide a relatively co
mplete discussion of Bayesian inferences for binomial regression with
emphasis on inferences for the probability of ''success.'' Furthermore
, we illustrate diagnostic tools, perform model selection among nonnes
ted models, and examine the sensitivity of the Bayesian methods.