model
{
	for(i in 1:N)
	{
		prece[i]<-1/desvar[i]
		Y[i] ~ dnorm(mu[i], prece[i])
mu[i] <- alpha + bhhpers*HHPERS[i]+bhhemp1*HHEMP1[i]+bedterhh*EDTERHH[i]+bagehh*AGEHH[i] + bsexhh*SEXHH[i]+ u[i] +v[i]

		u[i] ~ dnorm(0, precu)
	}

	v[1:N] ~ car.normal(adj[], weights[], num[], precv)

	precu ~ dgamma (a0,b0)
	precv ~ dgamma (a1,b1)

	alpha ~ dflat()
        bhhpers ~ dflat()
        bhhemp1 ~ dflat()
        bedterhh ~ dflat()
        bagehh ~ dflat()
        bsexhh ~ dflat()

	sigmau<-1/precu
	sigmav<-1/precv
}