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An Evaluation of Different Statistical Targets for Assembling Parallel Forms in Item Response Theory.
Usama S Ali1,2, Peter W van Rijn3
1Educational Testing Service, Princeton, NJ, USA.
Applied Psychological Measurement
|June 9, 2018
Summary
Creating parallel test forms requires careful consideration of statistical targets. Focusing solely on test characteristic curves (TCC) or test information functions (TIF) can lead to significant differences in difficulty or precision, which cannot always be corrected.
Area of Science:
- Psychometrics
- Educational Measurement
- Statistical Modeling
Background:
- Parallel test forms are crucial for reliable test development.
- Selecting appropriate statistical targets for test specifications is essential.
- Existing methods may prioritize either difficulty or precision, leading to imbalances.
Purpose of the Study:
- To investigate the performance of different statistical targets for test specifications.
- To evaluate the impact of test length, number of forms, and content specifications.
- To compare the outcomes of using test characteristic curve (TCC) and test information function (TIF) targets.
Main Methods:
- Simulations using a real item bank.
- Application of the two-parameter logistic model.
- Utilizing mixed integer linear programming for automated test assembly.
Main Results:
- TCC targets yield forms parallel in difficulty, but not necessarily precision.
- TIF targets yield forms parallel in precision, but not necessarily difficulty.
- Substantial differences in difficulty or precision can arise when focusing on only TCC or TIF.
Conclusions:
- Differences in test form difficulty can be addressed by equating, but precision differences cannot.
- Combining TCC and TIF targets, with adjusted relative importance, can eliminate these differences.
- A balanced approach to statistical targets is key for developing high-quality parallel test forms.
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