Testing for local dependency in dichotomous and polytomous item response models

Researchers studying item response models are often interested in examining the effects of local dependency on the validity of the resulting conclusio n from statistical inference. This paper focuses on the detection of local dependency. We provide a framework for viewing local dependency within dich otomous and polytomous items that are clustered by design, and present a te sting procedure that allows researchers to specifically identify individual item pairs that exhibit local dependency, while controlling for false posi tive rate. Simulation results from the study indicate that the proposed met hod is effective. In addition, a discussion of its relation to other existi ng methods is provided.