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Developing Multistage Tests Using D-Scoring Method.


ABSTRACT: The D-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number correct score computation and relaxed requirements for model sample sizes. Because of its unique combination of those merits, the D-scoring method has seen quick adoption in the educational and psychological measurement field. Because item-level difficulty information is available with the D-scoring method and item difficulties are reflected in test scores, it conceptually makes sense to use the D-scoring method with adaptive test designs such as multistage testing (MST). In this study, we developed and compared several versions of the MST mechanism using the D-scoring approach and also proposed and implemented a new framework for conducting MST simulation under the D-scoring method. Our findings suggest that the score recovery performance under MST with D-scoring was promising, as it retained score comparability across different MST paths. We found that MST using the D-scoring method can achieve improvements in measurement precision and efficiency over linear-based tests that use D-scoring method.

SUBMITTER: Han KCT 

PROVIDER: S-EPMC6713982 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Developing Multistage Tests Using <i>D</i>-Scoring Method.

Han Kyung Chris T KCT   Dimitrov Dimiter M DM   Al-Mashary Faisal F  

Educational and psychological measurement 20190422 5


The <i>D</i>-scoring method for scoring and equating tests with binary items proposed by Dimitrov offers some of the advantages of item response theory, such as item-level difficulty information and score computation that reflects the item difficulties, while retaining the merits of classical test theory such as the simplicity of number correct score computation and relaxed requirements for model sample sizes. Because of its unique combination of those merits, the <i>D</i>-scoring method has see  ...[more]

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