An open issue is whether a single, integrated measure (as evaluated in Table 4) fits the eyemovement data significantly better than separate measures for trigram, syntactic, and semantic surprisal (as evaluated in Table 3.
we are not able to investigate this hypothesis: our approach to testing the significance of factors requires nested models; the log-likelihood test (see Section 4) is only able to establish whether adding a factor to a model improves its fit; it cannot compare models with disjunct sets of factors (such as a model containing the integrated surprisal measure and one containing the three separate ones).