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Joo, Seang-Hwane; Lee, Philseok – Journal of Educational Measurement, 2022
Abstract This study proposes a new Bayesian differential item functioning (DIF) detection method using posterior predictive model checking (PPMC). Item fit measures including infit, outfit, observed score distribution (OSD), and Q1 were considered as discrepancy statistics for the PPMC DIF methods. The performance of the PPMC DIF method was…
Descriptors: Test Items, Bayesian Statistics, Monte Carlo Methods, Prediction
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Wind, Stefanie A.; Jones, Eli – Journal of Educational Measurement, 2019
Researchers have explored a variety of topics related to identifying and distinguishing among specific types of rater effects, as well as the implications of different types of incomplete data collection designs for rater-mediated assessments. In this study, we used simulated data to examine the sensitivity of latent trait model indicators of…
Descriptors: Rating Scales, Models, Evaluators, Data Collection
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Hou, Likun; de la Torre, Jimmy; Nandakumar, Ratna – Journal of Educational Measurement, 2014
Analyzing examinees' responses using cognitive diagnostic models (CDMs) has the advantage of providing diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this article, the Wald test is proposed to examine DIF in the context of CDMs. This study…
Descriptors: Test Bias, Models, Simulation, Error Patterns
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Clauser, Brian E.; Clyman, Stephen G.; Swanson, David B. – Journal of Educational Measurement, 1999
Two studies focused on aspects of the rating process in performance assessment. The first, which involved 15 raters and about 400 medical students, made the "committee" facet of raters working in groups explicit, and the second, which involved about 200 medical students and four raters, made the "rating-occasion" facet…
Descriptors: Error Patterns, Evaluation Methods, Evaluators, Higher Education
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Engelhard, George, Jr. – Journal of Educational Measurement, 1994
Rater errors (rater severity, halo effect, central tendency, and restriction of range) are described, and criteria are presented for evaluating rating quality based on a many-faceted Rasch (FACETS) model. Ratings of 264 compositions from the Eighth Grade Writing Test in Georgia by 15 raters illustrate the discussion. (SLD)
Descriptors: Criteria, Educational Assessment, Elementary Education, Elementary School Students