An IRT Modeling Approach for Assessing Item and Person Discrimination in Binary Personality Responses

Conventional item response theory (IRT) modeling of personality responses considers two item characteristics-location and discrimination-but only one person characteristic-location or trait level. An IRT modeling approach that jointly considers item and person discriminations, however, is thought to be more realistic and appropriate in this domain and has several potential advantages. This article develops a model of this type for unidimensional binary responses together with procedures for estimating item and person parameters and assessing model appropriateness (including person fit). A series of preliminary simulations suggests that the approach is feasible, and a real-data example illustrates the potential advantages with respect to the standard two-parameter model. Limitations of the proposal and further work are also discussed.