model {

	for (i in 1:length(insight)) {
		insight[i] ~ dcat(pi[i,])

		# cumulative category probabilities
		pi[i,1] <- cpi[i,1]
		for (k in 2:ncat) {
			pi[i,k] <- cpi[i,k] - cpi[i,k-1]
		}
		for (k in 1:(ncat-1)) {
			logit(cpi[i,k]) <- z[k] - cadd[i]
		}
		cpi[i,ncat] <- 1
	}
	z[1] ~ dnorm(0, .001)
	for (k in 2:(ncat-1)) {
		z[k] <- z[k-1] + dz[k]
		dz[k] ~ dunif(0, 50)
	}

}
