model
   {
      for( k in 1 : P ) {
         for( i in 1 : N ) {
            Y[i , k] ~ dnorm(m[i , k], tau1)
            m[i , k] <- mu + sign[T[i , k]] * phi / 2 + sign[k] * pi / 2 + delta[i]
            T[i , k] <- group[i] * (k - 1.5) + 1.5
         }
      }
      for( i in 1 : N ) {
         delta[i] ~ dnorm(0.0, tau2)
      }
      tau1 ~ dgamma(0.001, 0.001) sigma1 <- 1 / sqrt(tau1)
      tau2 ~ dgamma(0.001, 0.001) sigma2 <- 1 / sqrt(tau2)
      mu ~ dnorm(0.0, 1.0E-6)
      phi ~ dnorm(0.0, 1.0E-6)
      pi ~ dnorm(0.0, 1.0E-6)
      theta <- exp(phi)
      equiv <- step(theta - 0.8) - step(theta - 1.2)
   }