model { for( i in 1 : NG ) { for( j in 1 : TG ) { YG[i , j] ~ dnorm(muG[i , j],eps.tau) muG[i , j] <- betaG[i,1] + betaG[i,2] * (xG[j]-11) } betaG[i,1:2] ~ dmnorm(beta.muG[1:2],iSigma[1:2,1:2]) } for( i in 1 : NB ) { for( j in 1 : TB ) { YB[i , j] ~ dnorm(muB[i , j],eps.tau) muB[i , j] <- betaB[i,1] + betaB[i,2] * (xB[j]-11) } betaB[i,1:2] ~ dmnorm(beta.muB[1:2],iSigma[1:2,1:2]) } beta.muG[1:2] ~ dmnorm(meanG[1:2], precG[1:2, 1:2]) iSigma[1:2, 1:2] ~ dwish(R[1:2, 1:2], r) Sigma[1:2, 1:2] <- inverse(iSigma[1:2, 1:2]) sd0 <- sqrt(Sigma[1,1]) sd1 <- sqrt(Sigma[2,2]) corr <- Sigma[1,2]/sqrt(Sigma[1,1]*Sigma[2,2]) eps.tau <- exp(logtau) logtau ~ dflat() sigma <- 1 / sqrt(eps.tau) beta.muB[1:2] ~ dmnorm(meanB[1:2], precB[1:2, 1:2]) beta0BG <- beta.muB[1]-beta.muG[1] beta1BG <- beta.muB[2]-beta.muG[2] } list(xG = c(8,10,12,14), NG = 11, TG = 4, xB = c(8,10,12,14), NB = 16, TB = 4, YG = structure( .Data = c(21,20,21.5,23, 21,NA,NA,NA, 20.5,24,24.5,NA, 23.5,24.5,NA,NA, 21.5,23,22.5,NA, 20,21,NA,NA, 21.5,NA,NA,NA, 23,NA,NA,NA, 20,NA,NA,NA, 16.5,19,19,19.5, 24.5,25,28,NA), .Dim = c(11,4)),meanG = c(0, 0),r=4, R = structure(.Data = c(1, 0, 0,0.1), .Dim = c(2, 2)), precG = structure(.Data = c(1.0E-6, 0,0,1.0E-6), .Dim = c(2, 2) ), YB = structure( .Data = c( 26.0,NA,NA,NA, 21.5,22.5,NA,NA, 23.0,22.5,24.0,NA, 25.5,NA,NA,NA, 20.0,23.5,22.5,NA, 24.5,25.5,27.0,NA, 22.0,22.0,24.5,26.5, 24.0,21.5,NA,NA, 23.0,20.5,31.0,NA, 27.5,28.0,31.0,31.5, 23.0,NA,NA,NA, 21.5,23.5,24.0,NA, 17.0,NA,NA,NA, 22.5,25.5,25.5,NA, 23.0,NA,NA,NA, 22.0,21.5,23.5,25.0), .Dim = c(16,4)),meanB = c(0, 0), precB = structure(.Data = c(1.0E-6, 0,0,1.0E-6), .Dim = c(2, 2))) list(betaG = structure( .Data = c(18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5), .Dim = c(11, 2)), beta.muG = c(18, .5), iSigma = structure(.Data = c(1, 0, 0,1), .Dim = c(2, 2)), betaB = structure( .Data = c(18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5,18,.5), .Dim = c(16, 2)), beta.muB = c(18, .5), logtau = 0)