On the structure of ordered latent trait models.

Ordered item response models that are in common use can be divided into three groups, cumulative, sequential and adjacent categories model. The derivation and motivation of the models is typically based on the assumed presence of latent traits or underlying process models. In the construction frequently binary models play an important role. The objective of this paper is to give motivations for the models and to clarify the role of the binary models for the various types of ordinal models. It is investigated which binary models are included in an ordinal model but also how the models can be constructed from a sequence of binary models. In all the models one finds a Guttman space structure, which has previously been investigated in particular for the partial credit model. The consideration of the binary models adds to the interpretation of model parameters, which is helpful, in particular, in the case of the partial credit model, for which interpretation is less straightforward than for the other models. A specific topic that is addressed is the ordering of thresholds in the partial credit model because for some researchers reversed ordering is an anomaly, others disagree. It is argued that the ordering of thresholds is not a constitutive element of the partial credit model. • It is shown which binary models are contained in ordinal latent trait models. • It is also derived how models may be constructed from binary models. • It is shown that the binary models in the partial credit model are conditional models. • The link between ordinal models and Guttman variables is investigated. • It is demonstrated that the constructions given by Andrich (2013) are unnecessary difficult. • The role of the ordering of thresholds, which has been discussed controversially, is investigated. [ABSTRACT FROM AUTHOR]