specifying baseline prob prior in logit model

[wwiecek]

Currently logit.stan:62 has

  baseline ~ normal(0, 10);

  //hypermean priors:
  if(pooling_type > 0)
    target += prior_increment_real(prior_hypermean_fam, mu[1], prior_hypermean_val);
  else{
    for(k in 1:K)
      target += prior_increment_real(prior_hypermean_fam, eta[k], prior_hypermean_val);
  }

  //hyper-SD priors:
  if(pooling_type == 1)
    target += prior_increment_real(prior_hypersd_fam, tau[1], prior_hypersd_val);

  //fixed effect coefficients
  target += prior_increment_vec(prior_beta_fam, beta, prior_beta_val);

We should have one more category of flexible priors, i.e. baseline ~. We could also consider a hierarchical baseline by analogy with "mu & tau" type of models