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- W2056540971 abstract "Item response theory (IRT) models are a class of generalized mixed effect (GME) models used by psychometricians to describe the response behavior of individuals to a set of categorically scored items. The typical assumptions of IRT are Unidimensionality ( U ) of the random effect; Conditional ( or Local ) Independence ( CI ), the item responses are independent given the random effect; and Monotonicity ( M ), the probability of a correct response is a non-decreasing function of the random effect. The simple parametric models available in the psychometric literature have proved to be too restrictive in many data sets. Non-parametric regression models are a powerful tool for the estimation of non-linear curves, and have been used in IRT as a flexible way to model the item response function. This paper develops a new method for the non-parametric estimation of item response functions based on reversible-jump Markov Chain Monte Carlo, and demonstrates the practicality of the method by examining two data sets." @default.
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- W2056540971 date "2007-05-01" @default.
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- W2056540971 title "Modeling dichotomous item responses with free-knot splines" @default.
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- W2056540971 doi "https://doi.org/10.1016/j.csda.2006.04.021" @default.
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