bugs model for election analysis

county_binom_model.bugs.R

model {

  for(i in 1:n_obs){
    
    hrc_votes[i] ~ dbin(p[i], n_votes[i])
    p[i] ~ dbeta(alpha[i], beta[i])
    
    # reparameterization of the beta distribution taken from this site
    # http://bit.ly/2i880Oj
    
    alpha[i] <- mu[i] * phi[i]
    beta[i]  <- (1-mu[i]) * phi[i]

    logit(mu[i]) <-
      mu_inter +
      mu_white * white[i] +
      mu_age * age[i] +
      mu_diabetes * diabetes[i] + 
      mu_gini * gini[i] + 
      mu_income * income[i] +
      mu_high_school * high_school[i]+
      mu_uninsured * uninsured[i] +
      mu_unemployment * unemployment[i] +
      mu_crime * crime[i]
    
    log(phi[i]) <- 
      phi_inter + 
      phi_white * white[i] +
      phi_age * age[i] +
      phi_diabetes * diabetes[i] + 
      phi_gini * gini[i] + 
      phi_income * income[i] +
      phi_high_school * high_school[i]+
      phi_uninsured * uninsured[i] +
      phi_unemployment * unemployment[i] +
      phi_crime * crime[i] 
  
  }
  # diffuse, uninformative priors
  # used ~ dnorm(0, 0.00001) for every parameter
  # reminder: BUGS/JAGS uses precision (1/sigma) instead of sigma
}