Abstract

We give a historical introduction to item response theory, which places the work of Thurstone, Lord, Guttman and Coombs in a present-day perspective. The general assumptions of modern item response theory, local independence and monotonicity of response functions, are discussed, followed by a general framework for estimating item response models. Six classes of well-known item response models and recent developments are discussed: (1) models for dichotomous item scores; (2) models for polytomous item scores; (3) nonparametric models; (4) unfolding models; (5) multidimensional models; and (6) models with restrictions on the parameters. Finally, it is noted that item response theory has evolved from unidimensional scaling of items and measurement of persons to data analysis tools for complicated research designs.

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