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Conference Paper: A Not-So-Gentle Introduction to Item Response Theory

TitleA Not-So-Gentle Introduction to Item Response Theory
Authors
Issue Date2020
Citation
Research Seminar /Methodology and Statistics Workshop on Item Response Theory, Human Communication, Development and Information Sciences (CDIS), Faculty of Education, the University of Hong Kong, Hong Kong, China, 24 November 2020  How to Cite?
AbstractThis presentation will start with a comparison of classical test theory and item response theory (IRT), where the advantages of the former over the latter will be highlighted. It will be followed by a presentation of a number of both commonly and not-so-commonly encountered IRT models in the literature, which include models for dichotomous, polytomous, multiple-choice, rating, preference, and forced-choice data. General applications of IRT will be then discussed followed by some specific application examples. A brief demonstration of IRT analysis using R packages will follow. Finally, the presentation will conclude with a discussion of cognitive diagnosis models, which can be construed as a specific type of IRT model.
DescriptionInvited presentation
Persistent Identifierhttp://hdl.handle.net/10722/312538

 

DC FieldValueLanguage
dc.contributor.authorde la Torre, J-
dc.date.accessioned2022-04-27T08:00:07Z-
dc.date.available2022-04-27T08:00:07Z-
dc.date.issued2020-
dc.identifier.citationResearch Seminar /Methodology and Statistics Workshop on Item Response Theory, Human Communication, Development and Information Sciences (CDIS), Faculty of Education, the University of Hong Kong, Hong Kong, China, 24 November 2020 -
dc.identifier.urihttp://hdl.handle.net/10722/312538-
dc.descriptionInvited presentation-
dc.description.abstractThis presentation will start with a comparison of classical test theory and item response theory (IRT), where the advantages of the former over the latter will be highlighted. It will be followed by a presentation of a number of both commonly and not-so-commonly encountered IRT models in the literature, which include models for dichotomous, polytomous, multiple-choice, rating, preference, and forced-choice data. General applications of IRT will be then discussed followed by some specific application examples. A brief demonstration of IRT analysis using R packages will follow. Finally, the presentation will conclude with a discussion of cognitive diagnosis models, which can be construed as a specific type of IRT model.-
dc.languageeng-
dc.relation.ispartofHKU, Faculty of Education, Human Communication, Development and Information Sciences (CDIS) Research Seminar / Methodology and Statistics Workshop-
dc.titleA Not-So-Gentle Introduction to Item Response Theory-
dc.typeConference_Paper-
dc.identifier.emailde la Torre, J: j.delatorre@hku.hk-
dc.identifier.authorityde la Torre, J=rp02159-
dc.identifier.hkuros328205-

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