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) }