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Kim, Nana; Bolt, Daniel M. – Educational and Psychological Measurement, 2021
This paper presents a mixture item response tree (IRTree) model for extreme response style. Unlike traditional applications of single IRTree models, a mixture approach provides a way of representing the mixture of respondents following different underlying response processes (between individuals), as well as the uncertainty present at the…
Descriptors: Item Response Theory, Response Style (Tests), Models, Test Items
Arenson, Ethan A.; Karabatsos, George – Grantee Submission, 2017
Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…
Descriptors: Bayesian Statistics, Item Response Theory, Nonparametric Statistics, Models
Qian, Xiaoyu; Nandakumar, Ratna; Glutting, Joseoph; Ford, Danielle; Fifield, Steve – ETS Research Report Series, 2017
In this study, we investigated gender and minority achievement gaps on 8th-grade science items employing a multilevel item response methodology. Both gaps were wider on physics and earth science items than on biology and chemistry items. Larger gender gaps were found on items with specific topics favoring male students than other items, for…
Descriptors: Item Analysis, Gender Differences, Achievement Gap, Grade 8
Braeken, Johan; Blömeke, Sigrid – Assessment & Evaluation in Higher Education, 2016
Using data from the international Teacher Education and Development Study: Learning to Teach Mathematics (TEDS-M), the measurement equivalence of teachers' beliefs across countries is investigated for the case of "mathematics-as-a fixed-ability". Measurement equivalence is a crucial topic in all international large-scale assessments and…
Descriptors: Comparative Analysis, Bayesian Statistics, Test Bias, Teacher Education

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