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Latent variable models for an infinite sequence (or universe) of manifest variables that may be discrete, continuous, or a combination of both, are considered. A main theorem is presented that characterizes when it is possible to construct latent variable models that satisfy unidimensionality, monotonicity, conditional independence, and tail measurability. (SLD)

Stochastic ordering properties are investigated for a broad class of item response theory (IRT) models for which the monotone likelihood ratio does not hold. A taxonomy is given for nonparametric and parametric models for polytomous models based on the hierarchical relationship between the models. (SLD)