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Whittaker, Tiffany A.; Chang, Wanchen; Dodd, Barbara G. – Applied Psychological Measurement, 2012
When tests consist of multiple-choice and constructed-response items, researchers are confronted with the question of which item response theory (IRT) model combination will appropriately represent the data collected from these mixed-format tests. This simulation study examined the performance of six model selection criteria, including the…
Descriptors: Item Response Theory, Models, Selection, Criteria
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
Ip, Edward H. – Applied Psychological Measurement, 2010
The testlet response model is designed for handling items that are clustered, such as those embedded within the same reading passage. Although the testlet is a powerful tool for handling item clusters in educational and psychological testing, the interpretations of its item parameters, the conditional correlation between item pairs, and the…
Descriptors: Item Response Theory, Models, Test Items, Correlation
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
May, Henry – Journal of Educational and Behavioral Statistics, 2006
In this article, a new method is presented and implemented for deriving a scale of socioeconomic status (SES) from international survey data using a multilevel Bayesian item response theory (IRT) model. The proposed model incorporates both international anchor items and nation-specific items and is able to (a) produce student family SES scores…
Descriptors: Item Response Theory, Bayesian Statistics, Socioeconomic Status, Scaling