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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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Liang, Longjuan; Browne, Michael W. – Journal of Educational and Behavioral Statistics, 2015
If standard two-parameter item response functions are employed in the analysis of a test with some newly constructed items, it can be expected that, for some items, the item response function (IRF) will not fit the data well. This lack of fit can also occur when standard IRFs are fitted to personality or psychopathology items. When investigating…
Descriptors: Item Response Theory, Statistical Analysis, Goodness of Fit, Bayesian Statistics
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Magis, David – Journal of Educational and Behavioral Statistics, 2015
The purpose of this note is to study the equivalence of observed and expected (Fisher) information functions with polytomous item response theory (IRT) models. It is established that observed and expected information functions are equivalent for the class of divide-by-total models (including partial credit, generalized partial credit, rating…
Descriptors: Item Response Theory, Models, Statistics, Computation
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Drechsler, Jörg – Journal of Educational and Behavioral Statistics, 2015
Multiple imputation is widely accepted as the method of choice to address item-nonresponse in surveys. However, research on imputation strategies for the hierarchical structures that are typically found in the data in educational contexts is still limited. While a multilevel imputation model should be preferred from a theoretical point of view if…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Educational Research, Statistical Bias
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Castellano, Katherine E.; Ho, Andrew D. – Journal of Educational and Behavioral Statistics, 2015
Aggregate-level conditional status metrics (ACSMs) describe the status of a group by referencing current performance to expectations given past scores. This article provides a framework for these metrics, classifying them by aggregation function (mean or median), regression approach (linear mean and nonlinear quantile), and the scale that supports…
Descriptors: Expectation, Scores, Academic Achievement, Achievement Gains