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Wang, Shaojie; Zhang, Minqiang; Lee, Won-Chan; Huang, Feifei; Li, Zonglong; Li, Yixing; Yu, Sufang – Journal of Educational Measurement, 2022
Traditional IRT characteristic curve linking methods ignore parameter estimation errors, which may undermine the accuracy of estimated linking constants. Two new linking methods are proposed that take into account parameter estimation errors. The item- (IWCC) and test-information-weighted characteristic curve (TWCC) methods employ weighting…
Descriptors: Item Response Theory, Error of Measurement, Accuracy, Monte Carlo Methods
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Clauser, Brian E.; Kane, Michael; Clauser, Jerome C. – Journal of Educational Measurement, 2020
An Angoff standard setting study generally yields judgments on a number of items by a number of judges (who may or may not be nested in panels). Variability associated with judges (and possibly panels) contributes error to the resulting cut score. The variability associated with items plays a more complicated role. To the extent that the mean item…
Descriptors: Cutting Scores, Generalization, Decision Making, Standard Setting
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Andersson, Björn – Journal of Educational Measurement, 2016
In observed-score equipercentile equating, the goal is to make scores on two scales or tests measuring the same construct comparable by matching the percentiles of the respective score distributions. If the tests consist of different items with multiple categories for each item, a suitable model for the responses is a polytomous item response…
Descriptors: Equated Scores, Item Response Theory, Error of Measurement, Tests