A general item response theory model for unfolding unidimensional polytomous responses

The generalized graded unfolding model (GGUM) is developed. This model allo ws for either binary or graded responses and generalizes previous item resp onse models for unfolding in two useful ways. First, it implements a discri mination parameter that varies across items, which allows items to discrimi nate among respondents in different ways. Second, the GGUM permits response category threshold parameters to vary across items. A marginal maximum lik elihood algorithm is implemented to estimate GGUM item parameters, whereas person parameters are derived from an expected a posteriori technique. The applicability of the GGUM to common attitude testing situations is illustra ted with real data on student attitudes toward abortion.