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Titlebook: Essays on Item Response Theory; Anne Boomsma,Marijtje A. J. Duijn,Tom A. B. Snijde Book 2001 Springer Science+Business Media New York 2001

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书目名称Essays on Item Response Theory
编辑Anne Boomsma,Marijtje A. J. Duijn,Tom A. B. Snijde
视频video
丛书名称Lecture Notes in Statistics
图书封面Titlebook: Essays on Item Response Theory;  Anne Boomsma,Marijtje A. J. Duijn,Tom A. B. Snijde Book 2001 Springer Science+Business Media New York 2001
出版日期Book 2001
关键词Resampling; best fit; expectation–maximization algorithm; permutation tests
版次1
doihttps://doi.org/10.1007/978-1-4613-0169-1
isbn_softcover978-0-387-95147-8
isbn_ebook978-1-4613-0169-1Series ISSN 0930-0325 Series E-ISSN 2197-7186
issn_series 0930-0325
copyrightSpringer Science+Business Media New York 2001
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发表于 2025-3-21 20:56:51 | 显示全部楼层
The Growing Family of Rasch Models, and latent additivity. It is argued that concepts such as item homogeneity, person homogeneity, and unidimensionality do not hold for all generalizations of the Rasch model (RM). Four directions of generalizing the model are discussed: the multidimensional, the ordinal polytomous, the linear logis
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Conditional Independence and Differential Item Functioning in the Two-Parameter Logistic Model fit statistics are proposed that can be used to investigate conditional independence and differential item functioning globally and at the item level. The statistics are evaluated using their posterior predictive distribution.
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Differential Item Functioning Depending on General Covariatesmanifest predictors is a comprehensive framework for the detection of DIF. These models also support the investigation of the causes of DIF. In principle, the responses to every item in a test can be subject to DIF, and traditional IRT-based detection methods require one or more estimation runs for
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Expected Response Functionsn (pdf) for the response of an individual to a test item, given the values of certain parameters, classified as item parameters and person parameters (or abilities). In testing, there is typically a calibration phase, in which item parameters are estimated and abilities are ignored. This is followed
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A Logistic IRT Model for Decreasing and Increasing Item Characteristic Curvesare used for the measurement of latent abilities and unfolding models for the measurement of latent attitudes and preferences. The distinction between both types of measurement models is best represented by the shape of the item characteristic curve which is monotone increasing in the cumulative mod
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