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Levy, Roy – Educational Measurement: Issues and Practice, 2020
In this digital ITEMS module, Dr. Roy Levy describes Bayesian approaches to psychometric modeling. He discusses how Bayesian inference is a mechanism for reasoning in a probability-modeling framework and is well-suited to core problems in educational measurement: reasoning from student performances on an assessment to make inferences about their…
Descriptors: Bayesian Statistics, Psychometrics, Item Response Theory, Statistical Inference
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Paek, Insu; Cui, Mengyao; Öztürk Gübes, Nese; Yang, Yanyun – Educational and Psychological Measurement, 2018
The purpose of this article is twofold. The first is to provide evaluative information on the recovery of model parameters and their standard errors for the two-parameter item response theory (IRT) model using different estimation methods by Mplus. The second is to provide easily accessible information for practitioners, instructors, and students…
Descriptors: Item Response Theory, Computation, Factor Analysis, Statistical Analysis
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Deschaine, J. S.; Suits, B. H. – European Journal of Physics, 2008
Normal mode solutions for the perfectly flexible hanging cord problem have been known for over 200 years. More recently, theoretical results for a hanging cord with a point mass attached were presented. Here the theoretical results are tested experimentally using high-precision techniques which are accessible for use in an introductory laboratory.…
Descriptors: Physics, Item Response Theory, Science Instruction, College Science
Nering, Michael L., Ed.; Ostini, Remo, Ed. – Routledge, Taylor & Francis Group, 2010
This comprehensive "Handbook" focuses on the most used polytomous item response theory (IRT) models. These models help us understand the interaction between examinees and test questions where the questions have various response categories. The book reviews all of the major models and includes discussions about how and where the models…
Descriptors: Guides, Item Response Theory, Test Items, Correlation