lab:projects:a_working_example
## Estimate a multilevel mediation model model{ for (i in 1:n){ re[i, 1:5]~dmnorm(mure[i, 1:5], pre_cov[1:5,1:5]) mure[i,1]<-b[1,1]+b[1,2]*w[i] mure[i,2]<-b[2,1]+b[2,2]*w[i] mure[i,3]<-b[3,1]+b[3,2]*w[i] mure[i,4]<-b[4,1]+b[4,2]*w[i] mure[i,5]<-b[5,1]+b[5,2]*w[i] for (j in 1:mi[i]){ y[i,j] ~ dnorm(muy[i,j], pre_phi[1]) muy[i,j]<-re[j,1]+re[j,2]/re[j,3]*m[i,j]+re[j,4]*x[i,j] m[i,j] ~ dnorm(mum[i,j], pre_phi[2]) mum[i,j]<-re[j,5]+re[j,3]*x[i,j] } } for (i in 1:2){ pre_phi[i]~gamma(.001,.001) phi[i]<-1/pre_phi[i] } pre_cov[1:5,1:5]~dwish(R[1:5,1:5], 5) cov[1:5,1:5]<-inverse(pre_cov[1:5,1:5]) for (i in 1:5){ for (j in 1:2){ b[i,j]~dnorm(0, .001) } } } ## initial values list(pre_phi=c(1,1), phi=c(1,1), b=structure(.Data =c( 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0), .Dim = c(5,2)), cov=structure(.Data =c(1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1, 0.5, 0.5, 0.5, 0.5, 0.5, 1), .Dim = c(5,5))) ## data list(mi=c(100, 100, 100, 100, 100, 100, 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lab/projects/a_working_example.txt · Last modified: 2016/01/24 09:48 by 127.0.0.1