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如题不多说直接看下面文章题目和摘要：
《Confirmatory Multidimensional IRT Unfolding Models for Graded-Response Items》
Abstract
Most unfolding item response models for graded-response items are unidimensional. When
there are multiple tests of graded-response items, unidimensional unfolding models become
inefficient. To resolve this problem, the authors developed the confirmatory multidimensional
generalized graded unfolding model, which is a multidimensional extension of the generalized
graded unfolding model, and conducted a series of simulations to evaluate its parameter recovery.
The simulation study on between-item multidimensionality demonstrated that the parameters
of the new model can be recovered fairly well with the WinBUGS program. The Tattoo
Attitude Questionnaire, with three subscales, was analyzed to demonstrate the advantages of
the new model over the unidimensional model in obtaining a better model-data fit, a higher test
reliability, and a stronger correlation between latent traits. Discussion on potential applications
and suggestion for future studies are provided.
Keywords
item response theory, unfolding, multidimensional models, ideal-point, Bayesian, gradedresponse
items
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