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Feuerstahler, Leah; Wilson, Mark – Journal of Educational Measurement, 2019
Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated…
Descriptors: Item Response Theory, Models, Scores, Comparative Analysis
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Finch, Holmes – Practical Assessment, Research & Evaluation, 2022
Researchers in many disciplines work with ranking data. This data type is unique in that it is often deterministic in nature (the ranks of items "k"-1 determine the rank of item "k"), and the difference in a pair of rank scores separated by "k" units is equivalent regardless of the actual values of the two ranks in…
Descriptors: Data Analysis, Statistical Inference, Models, College Faculty
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Verhelst, Norman D. – Scandinavian Journal of Educational Research, 2012
When using IRT models in Educational Achievement Testing, the model is as a rule too simple to catch all the relevant dimensions in the test. It is argued that a simple model may nevertheless be useful but that it can be complemented with additional analyses. Such an analysis, called profile analysis, is proposed and applied to the reading data of…
Descriptors: Multidimensional Scaling, Profiles, Item Response Theory, Achievement Tests
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Sun, Xiang; Allison, Carrie; Auyeung, Bonnie; Matthews, Fiona E.; Norton, Samuel; Baron-Cohen, Simon; Brayne, Carol – Journal of Autism and Developmental Disorders, 2014
Limited studies have investigated the latent autistic traits in the mainland Chinese population for autism spectrum conditions (ASC). This study explored the psychometric properties of a Mandarin Chinese version of the CAST in a sample consisting of 737 children in mainstream schools and 50 autistic cases. A combination of categorical data factor…
Descriptors: Psychometrics, Mandarin Chinese, Autism, Pervasive Developmental Disorders
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Li, Ying; Jiao, Hong; Lissitz, Robert W. – Journal of Applied Testing Technology, 2012
This study investigated the application of multidimensional item response theory (IRT) models to validate test structure and dimensionality. Multiple content areas or domains within a single subject often exist in large-scale achievement tests. Such areas or domains may cause multidimensionality or local item dependence, which both violate the…
Descriptors: Achievement Tests, Science Tests, Item Response Theory, Measures (Individuals)
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Perry, John L.; Nicholls, Adam R.; Clough, Peter J.; Crust, Lee – Measurement in Physical Education and Exercise Science, 2015
Despite the limitations of overgeneralizing cutoff values for confirmatory factor analysis (CFA; e.g., Marsh, Hau, & Wen, 2004), they are still often employed as golden rules for assessing factorial validity in sport and exercise psychology. The purpose of this study was to investigate the appropriateness of using the CFA approach with these…
Descriptors: Factor Analysis, Structural Equation Models, Goodness of Fit, Sport Psychology
Reynolds, Thomas J. – 1976
A method of factor extraction specific to a binary matrix, illustrated here as a person-by-item response matrix, is presented. The extraction procedure, termed ERGO, differs from the more commonly implemented dimensionalizing techniques, factor analysis and multidimensional scaling, by taking into consideration item difficulty. Utilized in the…
Descriptors: Discriminant Analysis, Factor Analysis, Item Analysis, Matrices
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Yao, Lihua; Schwarz, Richard D. – Applied Psychological Measurement, 2006
Multidimensional item response theory (IRT) models have been proposed for better understanding the dimensional structure of data or to define diagnostic profiles of student learning. A compensatory multidimensional two-parameter partial credit model (M-2PPC) for constructed-response items is presented that is a generalization of those proposed to…
Descriptors: Models, Item Response Theory, Markov Processes, Monte Carlo Methods