ERIC Number: EJ1134149
Record Type: Journal
Publication Date: 2017-Apr
Abstractor: As Provided
Adjacent-Categories Mokken Models for Rater-Mediated Assessments
Wind, Stefanie A.
Educational and Psychological Measurement, v77 n2 p330-350 Apr 2017
Molenaar extended Mokken's original probabilistic-nonparametric scaling models for use with polytomous data. These polytomous extensions of Mokken's original scaling procedure have facilitated the use of Mokken scale analysis as an approach to exploring fundamental measurement properties across a variety of domains in which polytomous ratings are used, including rater-mediated educational assessments. Because their underlying item step response functions (i.e., category response functions) are defined using cumulative probabilities, polytomous Mokken models can be classified as cumulative models based on the classifications of polytomous item response theory models proposed by several scholars. In order to permit a closer conceptual alignment with educational performance assessments, this study presents an adjacent-categories variation on the polytomous monotone homogeneity and double monotonicity models. Data from a large-scale rater-mediated writing assessment are used to illustrate the adjacent-categories approach, and results are compared with the original formulations. Major findings suggest that the adjacent-categories models provide additional diagnostic information related to individual raters' use of rating scale categories that is not observed under the original formulation. Implications are discussed in terms of methods for evaluating rating quality.
Descriptors: Nonparametric Statistics, Scaling, Models, Item Response Theory, Probability, Educational Assessment, Writing Tests, Comparative Analysis, Classification
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Publication Type: Journal Articles; Reports - Research
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