model
{
#  
#  X[,1] = DW-NOMINATE 1st Dimension
#  X[,2] = DW-NOMINATE 2nd Dimension
#  X[,3] = 1 if Republican, 0 otherwise
#  X[,4] = 1 if South (CQ def.), 0 otherwise
#  
#  PRIORS
#
         tau ~ dgamma(1.0E-1, 1.0E-1)
         for (k in 1 : 3) { beta[k] ~ dnorm(0,0.001)} # vague priors
#	  
# LIKELIHOOD	
#
    for (i in 1 : 434)  # loop over congressional districts
    {     
#
         X[i,1] ~ dnorm( mu[i] , tau)
         mu[i] <- beta[1]+X[i,3]*beta[2]+X[i,2]*beta[3]
    }  
    sigma <- sqrt(1/tau)
#
 }