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Titlebook: Explanatory Item Response Models; A Generalized Linear Paul Boeck,Mark Wilson Book 2004 Springer Science+Business Media New York 2004 SAS.p

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發(fā)表于 2025-3-21 19:19:50 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Explanatory Item Response Models
副標(biāo)題A Generalized Linear
編輯Paul Boeck,Mark Wilson
視頻videohttp://file.papertrans.cn/320/319355/319355.mp4
概述Gives a new and integrated introduction to item response models (predominantly used in measurement applications in psychology, education, and other social science areas) from the viewpoint of the stat
叢書名稱Statistics for Social and Behavioral Sciences
圖書封面Titlebook: Explanatory Item Response Models; A Generalized Linear Paul Boeck,Mark Wilson Book 2004 Springer Science+Business Media New York 2004 SAS.p
描述This edited volume gives a new and integrated introduction to item re- sponse models (predominantly used in measurement applications in psy- chology, education, and other social science areas) from the viewpoint of the statistical theory of generalized linear and nonlinear mixed models. Moreover, this new framework aHows the domain of item response mod- els to be co-ordinated and broadened to emphasize their explanatory uses beyond their standard descriptive uses. The basic explanatory principle is that item responses can be modeled as a function of predictors of various kinds. The predictors can be (a) char- acteristics of items, of persons, and of combinations of persons and items; they can be (b) observed or latent (of either items or persons); and they can be (c) latent continuous or latent categorical. Thus, a broad range of models can be generated, including a wide range of extant item response models as weH as some new ones. Within this range, models with explana- tory predictors are given special attention, but we also discuss descriptive models. Note that the ‘item responses‘ that we are referring to are not just the traditional ‘test data,‘ but are broadly conceived as ca
出版日期Book 2004
關(guān)鍵詞SAS; psychometrics; statistical theory
版次1
doihttps://doi.org/10.1007/978-1-4757-3990-9
isbn_softcover978-1-4419-2323-3
isbn_ebook978-1-4757-3990-9Series ISSN 2199-7357 Series E-ISSN 2199-7365
issn_series 2199-7357
copyrightSpringer Science+Business Media New York 2004
The information of publication is updating

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https://doi.org/10.1007/978-1-4757-3990-9SAS; psychometrics; statistical theory
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Preispolitik im ZahlungsverkehrIn all models discussed thus far in this volume, it has been assumed that the random person weights .. follow a normal distribution with mean 0 and covariance matrix .: ..
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Mixture ModelsIn all models discussed thus far in this volume, it has been assumed that the random person weights .. follow a normal distribution with mean 0 and covariance matrix .: ..
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https://doi.org/10.1007/978-3-7091-7913-0rray of models and data that one can find in the area of item response modeling, (b) to explore different contexts of data analysis than the ‘test data’ context to which item response models are traditionally applied, and (c) to place these models in a larger statistical framework that will enable t
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https://doi.org/10.1007/978-3-7091-7865-2ome of them are more complex than the common item response models. On the one hand, all four models provide a measurement of individual differences, but on the other hand we use the models to demonstrate how the effect of person characteristics and of item design factors can be investigated. The mod
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