model
{
   for(i in 1:nObs) 
   {

      mu[i] <- beta0 + UV[idnum[i],1] + (beta1 + UV[idnum[i],2])*sweeks[i]
      weight[i] ~ dnorm(mu[i],tauEps)	
   }	

  
   for (j in 1:2)
   {
      UVmean[j] <- 0
   }

   for (iSubj in 1:nSubj)
   {
      UV[iSubj,1:2] ~ dmnorm(UVmean[1:2],Omega[1:2,1:2])
   }  

   beta0  ~ dnorm(0,1.0E-8)
   beta1  ~ dnorm(0,1.0E-8)

   Omega[1:2,1:2] ~ dwish(R[,],2)

   R[1,1] <- 0.01 ; R[1,2] <- 0
   R[2,1] <- 0     ; R[2,2] <- 0.01

   tauEps ~ dgamma(0.01,0.01)

   invOmega[1:2,1:2] <- inverse(Omega[,])
   sigU <- sqrt(invOmega[1,1])
   sigV <- sqrt(invOmega[2,2])
   sigEps <- 1/sqrt(tauEps)
}