Journal article
IRT Characteristic Curve Linking Methods Weighted by Information for Mixed-Format Tests
Applied measurement in education, Vol.37(4), pp.377-390
10/2024
DOI: 10.1080/08957347.2024.2424547
Abstract
To reduce the impact of parameter estimation errors on IRT linking results, recent work introduced two information-weighted characteristic curve methods for dichotomous items. These two methods showed outstanding performance in both simulation and pseudo-form pseudo-group analysis. The current study expands upon the concept of information weighting in the context of linking mixed-format tests. Three new linking methods were proposed, including category-information-weighted characteristic curve (CWCC), item-information-weighted characteristic curve (IWCC), and test-information-weighted characteristic curve (TWCC) methods. Both a simulation study and a pseudo-form pseudo-group analysis were conducted to evaluate their relative performances under the non-equivalent groups with anchor test design. In general, IWCC and TWCC outperformed their respective counterparts, whereas the advantage of CWCC was not readily apparent. Among the three new methods, IWCC and TWCC showed better performance. Practical recommendations and future directions are discussed.
Details
- Title: Subtitle
- IRT Characteristic Curve Linking Methods Weighted by Information for Mixed-Format Tests
- Creators
- Shaojie Wang - Guangdong University of EducationWon-Chan Lee - University of IowaMinqiang Zhang - South China Normal UniversityLixin Yuan - Guangdong University of Education
- Resource Type
- Journal article
- Publication Details
- Applied measurement in education, Vol.37(4), pp.377-390
- Publisher
- ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD
- DOI
- 10.1080/08957347.2024.2424547
- ISSN
- 0895-7347
- eISSN
- 1532-4818
- Grant note
- Guangdong Educational Science Plan: 2023GXJK123
The work was supported by the Guangdong Educational Science Plan [2023GXJK123].
- Language
- English
- Electronic publication date
- 11/04/2024
- Date published
- 10/2024
- Academic Unit
- Psychological and Quantitative Foundations
- Record Identifier
- 9984743400402771
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