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Titlebook: Handbook of Diagnostic Classification Models; Models and Model Ext Matthias von Davier,Young-Sun Lee Book 2019 The Editor(s) (if applicable

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書目名稱Handbook of Diagnostic Classification Models
副標(biāo)題Models and Model Ext
編輯Matthias von Davier,Young-Sun Lee
視頻videohttp://file.papertrans.cn/422/421151/421151.mp4
概述A major collection that describes the state of the art of diagnostic classification models (DCMs).Provides chapters on the majority of popular DCMs as well as cutting edge model extensions developed b
叢書名稱Methodology of Educational Measurement and Assessment
圖書封面Titlebook: Handbook of Diagnostic Classification Models; Models and Model Ext Matthias von Davier,Young-Sun Lee Book 2019 The Editor(s) (if applicable
描述.This handbook provides an overview of major developments around diagnostic classification models (DCMs) with regard to modeling, estimation, model checking, scoring, and applications. It brings together not only the current state of the art, but also the theoretical background and models developed for diagnostic classification. The handbook also offers applications and special topics and practical guidelines how to plan and conduct research studies with the help of DCMs.. . Commonly used models in educational measurement and psychometrics typically assume a single latent trait or at best a small number of latent variables that are aimed at describing individual differences in observed behavior. While this allows simple rankings of test takers along one or a few dimensions, it does not provide a detailed picture of strengths and weaknesses when assessing complex cognitive skills.. . DCMs, on the other hand, allow the evaluation of test taker performance relative to a potentially large number of skill domains. Most diagnostic models provide a binary mastery/non-mastery classification for each of the assumed test taker attributes representing these skill domains. Attribute profiles c
出版日期Book 2019
關(guān)鍵詞Educational measurement; LCDM; G-DINA; Psychometrics; Diagnostic Classification Models; GDM; Adaptive test
版次1
doihttps://doi.org/10.1007/978-3-030-05584-4
isbn_ebook978-3-030-05584-4Series ISSN 2367-170X Series E-ISSN 2367-1718
issn_series 2367-170X
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Handbook of Diagnostic Classification Models978-3-030-05584-4Series ISSN 2367-170X Series E-ISSN 2367-1718
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Bayesian Networks from .), Genie (BayesFusion, LLC, Genie, 2017. Retrieved from . (Bayesian network Computer Software)) and BayesiaLab (Bayesia, Bayesialab, 2017. Retrieved from . (Bayesian Network Computer Software)) as well as a number of free software packages.
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The General Diagnostic Model a wide range of diagnostic models, as well as item response theory (IRT), multidimensional IRT (MIRT), latent class models, located latent class models, multiple group and mixture versions of these models, as well as multilevel, and longitudinal extensions of these. This chapter introduces the GDM
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