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50 Years of ERIC
50 Years of ERIC
The Education Resources Information Center (ERIC) is celebrating its 50th Birthday! First opened on May 15th, 1964 ERIC continues the long tradition of ongoing innovation and enhancement.

Learn more about the history of ERIC here. PDF icon

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Mao, Xiulin; Harring, Jeffrey R.; Hancock, Gregory R. – Educational and Psychological Measurement, 2015
Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…
Descriptors: Structural Equation Models, Error of Measurement, Algebra, Statistical Analysis
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Raykov, Tenko; Marcoulides, George A. – Educational and Psychological Measurement, 2015
A direct approach to point and interval estimation of Cronbach's coefficient alpha for multiple component measuring instruments is outlined. The procedure is based on a latent variable modeling application with widely circulated software. As a by-product, using sample data the method permits ascertaining whether the population discrepancy…
Descriptors: Computation, Statistical Analysis, Reliability, Models
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Wang, Wen-Chung; Chen, Hui-Fang; Jin, Kuan-Yu – Educational and Psychological Measurement, 2015
Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to…
Descriptors: Item Response Theory, Test Format, Language Usage, Test Items
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Lai, Emily R.; Wolfe, Edward W.; Vickers, Daisy – Educational and Psychological Measurement, 2015
This report summarizes an empirical study that addresses two related topics within the context of writing assessment--illusory halo and how much unique information is provided by multiple analytic scores. Specifically, we address the issue of whether unique information is provided by analytic scores assigned to student writing, beyond what is…
Descriptors: Writing Tests, Scores, Bias, Holistic Approach
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Kopf, Julia; Zeileis, Achim; Strobl, Carolin – Educational and Psychological Measurement, 2015
Differential item functioning (DIF) indicates the violation of the invariance assumption, for instance, in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g., for the reference and the focal group) is necessary. In the Rasch model,…
Descriptors: Test Items, Equated Scores, Test Bias, Item Response Theory
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France, Stephen L.; Batchelder, William H. – Educational and Psychological Measurement, 2015
Cultural consensus theory (CCT) is a data aggregation technique with many applications in the social and behavioral sciences. We describe the intuition and theory behind a set of CCT models for continuous type data using maximum likelihood inference methodology. We describe how bias parameters can be incorporated into these models. We introduce…
Descriptors: Maximum Likelihood Statistics, Test Items, Difficulty Level, Test Theory
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Egberink, Iris J. L.; Meijer, Rob R.; Tendeiro, Jorge N. – Educational and Psychological Measurement, 2015
A popular method to assess measurement invariance of a particular item is based on likelihood ratio tests with all other items as anchor items. The results of this method are often only reported in terms of statistical significance, and researchers proposed different methods to empirically select anchor items. It is unclear, however, how many…
Descriptors: Personality Measures, Computer Assisted Testing, Measurement, Test Items
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Choi, In-Hee; Wilson, Mark – Educational and Psychological Measurement, 2015
An essential feature of the linear logistic test model (LLTM) is that item difficulties are explained using item design properties. By taking advantage of this explanatory aspect of the LLTM, in a mixture extension of the LLTM, the meaning of latent classes is specified by how item properties affect item difficulties within each class. To improve…
Descriptors: Classification, Test Items, Difficulty Level, Statistical Analysis