model {

  # Uninformative priors for logistic regression weights  
  logoffset ~ dnorm(0.0, 0.01)
  logdegree ~ dnorm(0.0, 0.1)
  loglit ~ dnorm(0.0, 0.01)
  logito ~ dnorm(0.0, 0.01)
  loguetz ~ dnorm(0.0, 0.01)

  for( i in 1 : M ) {
        val[i] <- logoffset + loglit*(lit[i]-1) + logito*(ito[i]-1) + loguetz*(uetz[i]-1) + logdegree*degree[i]
	ppiprior[i] <- 1 / (1 + exp(val[i]))
	ppi[i] ~ dbern(ppiprior[i])
  }

}