	
		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)
		}