model {
  for(i in 1:length(pair_diff)) {
    pair_diff[i] ~ dt( mu_diff , tau_diff , nu )
  }
  diff_pred ~ dt( mu_diff , tau_diff , nu )
  eff_size <- (mu_diff - comp_mu) / sigma_diff

  mu_diff ~ dnorm( mean_mu , precision_mu )
  tau_diff <- 1/pow( sigma_diff , 2 )
  sigma_diff ~ dunif( sigma_low , sigma_high )
  # A trick to get an exponentially distributed prior on nu that starts at 1.
  nu <- nuMinusOne + 1
  nuMinusOne ~ dexp(1/29)
}