@bgoodri @Bob_Carpenter @jonah I have two questions related to your nice and very useful write up/tutorial on hierarchical partial pooling with repeated binary trials available here.

Where can I find more detail about the likelihood function, prior, and hyper prior for the partial pooling example? It is not entirely clear to me what these would look like. The other examples on complete and no pooling have these clearly stated. Also, shouldn’t there be a hyperprior? I thought this to be the case when I read “the hierarchical model places a prior on the [player] abilities with parameters that are themselves estimated.”

The first code block you got
fit_partialpool < stan_glmer(cbind(Hits, AB  Hits) ~ (1  Player), data = bball, family = binomial("logit"), prior_intercept = wi_prior, seed = SEED)
Shouldn’t there also be a prior on alpha_n? thus
fit_partialpool < stan_glmer(cbind(Hits, AB  Hits) ~ (1  Player), prior=wi_prior, data = bball, family = binomial("logit"), prior_intercept = wi_prior, seed = SEED)
Thanks so much for your help!