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diff --git a/tests/examplefiles/example.jag b/tests/examplefiles/example.jag
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-# lsat.jags example from classic-bugs examples in JAGS
-# See http://sourceforge.net/projects/mcmc-jags/files/Examples/2.x/
-var
-   response[R,T], m[R], culm[R], alpha[T], a[T], theta[N], r[N,T],
-   p[N,T], beta, theta.new, p.theta[T], p.item[R,T], P.theta[R];
-data {
-   for (j in 1:culm[1]) {
-      r[j, ] <- response[1, ];
-   }
-   for (i in 2:R) {
-      for (j in (culm[i - 1] + 1):culm[i]) {
-         r[j, ] <- response[i, ];
-      }
-   }
-}
-model {
-  # 2-parameter Rasch model
-  for (j in 1:N) {
-     for (k in 1:T) {
-        probit(p[j,k]) <- delta[k]*theta[j] - eta[k];
-        r[j,k] ~ dbern(p[j,k]);
-     }
-     theta[j] ~ dnorm(0,1);
-  }
-
-  # Priors
-  for (k in 1:T) {
-     eta[k] ~ dnorm(0,0.0001);       
-     e[k] <- eta[k] - mean(eta[]);  # sum-to-zero constraint
-
-     delta[k] ~ dnorm(0,1) T(0,);   # constrain variance to 1, slope +ve
-     d[k] <- delta[k]/pow(prod(delta), 1/T); # PRODUCT_k (d_k) = 1
- 
-     g[k] <- e[k]/d[k];   # equivalent to B&A's threshold parameters
-  }
-
-  # Compute probability of response pattern i, for later use in computing G^2
-  theta.new ~ dnorm(0,1);          # ability parameter for random student 
-  for(k in 1:T) {
-       probit(p.theta[k]) <- delta[k]*theta.new - eta[k];
-       for(i in 1:R) {
-          p.item[i,k] <- p.theta[k]^response[i,k] * (1-p.theta[k])^(1-response[i,k]);
-       }
-  } 
-  for(i in 1:R) {    
-     P.theta[i] <- prod(p.item[i,])
-  }
-}