Publication: Multidimensional Test Assembly Using Mixed-Integer Linear Programming: An Application of Kullback–Leibler Information
Multidimensional Test Assembly Using Mixed-Integer Linear Programming: An Application of Kullback–Leibler Information
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Debeer, D., van Rijn, P. W., & Ali, U. S. (2020). Multidimensional Test Assembly Using Mixed-Integer Linear Programming: An Application of Kullback–Leibler Information. Applied Psychological Measurement, 44(1), 17–32. https://doi.org/10.1177/0146621619827586
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Many educational testing programs require different test forms with minimal or no item overlap. At the same time, the test forms should be parallel in terms of their statistical and content-related properties. A well-established method to assemble parallel test forms is to apply combinatorial optimization using mixed-integer linear programming (MILP). Using this approach, in the unidimensional case, Fisher information (FI) is commonly used as the statistical target to obtain parallelism. In the multidimensional case, however, FI is a
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- van Rijn, Peter W
- Ali, Usama S
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Debeer, D., van Rijn, P. W., & Ali, U. S. (2020). Multidimensional Test Assembly Using Mixed-Integer Linear Programming: An Application of Kullback–Leibler Information. Applied Psychological Measurement, 44(1), 17–32. https://doi.org/10.1177/0146621619827586