Browsing by Author "Chang, Hua-Hua"

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Equated Pooled Booklet Method in DIF Testing
(2013-06-01)
Cheng, Ying
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Chen, Peihua
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Qian, Jiahe
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Chang, Hua-Hua
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交大名義發表
Differential item functioning (DIF) analysis is an important step in the data analysis of large-scale testing programs. Nowadays, many such programs endorse matrix sampling designs to reduce the load on examinees, such as the balanced incomplete block (BIB) design. These designs pose challenges to the traditional DIF analysis methods. For example, as difficulty levels often vary across booklets, examinees with same booklet scores may be disparate in ability. Consequently, DIF procedures based on matching total scores at the booklet level may cause misplacement of examinees and inflation in measurement errors. Therefore, modification to traditional DIF procedures to better accommodate the BIB design becomes important. This article introduces modification of current simultaneous item bias test (SIBTEST) procedure for the DIF analysis method when multiple booklets are used. More specifically, examinees will be pooled across booklets, and the matching will be based on transformed booklet scores after common block equating/linking. Simulations are conducted to compare the performance of this new method, the equated pooled booklet method against that of the current pooled booklet method, in terms of both Type I error control and power. Four factors are considered in the simulationthe DIF effect size, item difficulty, impact, and the length of common block. Results show that the equated pooled booklet method in general improves power while keeping Type I error under control. The advantage of the new method is the most pronounced when the traditional method struggles, for example, when the item is difficult or there is impact.
Item Selection for the Development of Parallel Forms From an IRT-Based Seed Test Using a Sampling and Classification Approach
(2012-12-01)
Chen, Pei-Hua
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Chang, Hua-Hua
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Wu, Haiyan
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應用化學系
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管理科學系
Two sampling-and-classification-based procedures were developed for automated test assembly: the Cell Only and the Cell and Cube methods. A simulation study based on a 540-item bank was conducted to compare the performance of the procedures with the performance of a mixed-integer programming (MIP) method for assembling multiple parallel test forms. The study investigated the statistical equivalence of the forms generated by the three test assembly methods (Cell Only, Cell and Cube, and MIP) in terms of test information functions, test characteristic curves, mean square deviations, and practical constraints, such as content balancing and nonoverlap among forms. The results indicated that the 13-point MIP method outperformed the other two methods in terms of the "closeness" test information functions between the reference form and the assembled parallel tests. Regarding test characteristic curves, the Cell Only and Cell and Cube methods yielded more similar test characteristic curves than the MIP method. Constraining test information functions apparently does not guarantee that the assembled forms will yield similar test characteristic curves. Overall, the Cell Only and Cell and Cube methods have the potential to provide results similar to the optimization approach.