var  r[N], p[N], x[N], n[N], alpha, alpha.star, beta, r.hat[N], llike[N], 
	llike.sat[N], D;
model {
   for (i in 1:N) {
      r[i] ~ dbin(p[i], n[i]);
      cloglog(p[i]) <- alpha.star + beta*(x[i]-mean(x[]));
      # log likelihood for sample i & saturated log-likelihood:
      llike[i]     <- r[i]*log(p[i]) + (n[i]-r[i])*log(1-p[i]);  
      llike.sat[i] <- r[i]*log(r[i]/n[i]) + (n[i]-r[i])*log(1-r[i]/n[i]);
      r.hat[i] <- p[i]*n[i];  # fitted values
    }
    alpha.star ~ dnorm(0.0, 1.0E-3);
    beta      ~ dnorm(0.0, 1.0E-3);
    alpha     <- alpha.star - beta*mean(x[]);

    D <- 2 * (sum(llike.sat[]) - sum(llike[]));
}