model{
   for(i in 1:Ns){
      k[i]~dbern(p[i])
      pred[i]~dbern(p[i])
      x[i]<-inprod(IV[i,],b)
      p[i]<-ilogit(x[i]+error[i])
   }
   # Prior
   for(i in 1:Ns){
      error[i]~dnorm(0,lambda.err)
   }
   lambda.err~dgamma(0.001,0.001)
   for(j in 1:Nt){
      b[j]~dnorm(0,0.0001)
   }
}