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Exploring levels of performance using the mixture Rasch model for standard setting

Author(s): Hong Jiao | Robert W. Lissitz | George Macready | Shudong Wang | Senfeng Liang

Journal: Psychological Test and Assessment Modeling
ISSN 2190-0493

Volume: 53;
Issue: 4;
Start page: 499;
Date: 2011;
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Keywords: mixture Rasch model | standard setting | proficiency classification | model-based classi-fication | performance standards

This study proposes a method using the mixture Rasch model to set performance standards. The mixture Rasch model classifies examinees into qualitatively distinct latent groups based on the information in the response patterns and quantifies individual differences within-group utilizing a continuous latent trait.The goals of this study are twofold. One is to demonstrate an application of the mixture Rasch model to statistically validate the performance proficiency levels set by policy makers and reviewed by content experts. The other is to demonstrate how performance cut scores can be obtained based on the results from data analysis using the mixture Rasch model. In general, this study presents a mixture Rasch model-based approach for setting performance standards which is expected to facilitate the standard setting process by providing the data driven information re-lated to the policy specified performance levels and the performance cut scores set by the panelists.
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