Conditional independence is a fundamental principle in latent variable modeling and item response theory. Violations of this principle, commonly known as local item dependencies, are put in a test information perspective, and sharp bounds on these violations are defined. A modeling approach is proposed that makes use of a mixture representation of these boundaries to account for the local dependence problem by finding a balance between independence on the one side and absolute dependence on the other side. In contrast to alternative approaches, the nature of the proposed boundary mixture model does not necessitate a change in formulation of the typical item characteristic curves used in item response theory. This has attractive interpretational advantages and may be useful for general test construction purposes.

In a number of psychological studies, answers to reasoning vignettes have been shown to result from both intuitive and deliberate response processes. This paper utilizes a psychometric model to separate these two response tendencies. An experimental application shows that the proposed model facilitates the analysis of dual-process item responses and the assessment of individual-difference factors, as well as conditions that favor one response tendency over another one.