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Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection
Published online by Cambridge University Press: 01 January 2025
Abstract
Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the abilities. Both the theoretical analyses and the studies of simulated data in this paper suggest that the criteria of A-optimality and D-optimality lead to the most accurate estimates when all abilities are intentional, with the former slightly outperforming the latter. The criterion of E-optimality showed occasional erratic behavior for this case of adaptive testing, and its use is not recommended. If some of the abilities are nuisances, application of the criterion of As-optimality (or Ds-optimality), which focuses on the subset of intentional abilities is recommended. For the measurement of a linear combination of abilities, the criterion of c-optimality yielded the best results. The preferences of each of these criteria for items with specific patterns of parameter values was also assessed. It was found that the criteria differed mainly in their preferences of items with different patterns of values for their discrimination parameters.
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- This article distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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- Copyright © 2008 The Author(s)
Footnotes
The first author is now at the Department of Methodology and Statistics, Statistics, Faculty of Social Sciences, Utrecht University, Heidelberglaan 1, 3854 Utrecht, The Netherlands. The second author is now at Research Department, CTB/McGraw-Hill, Monterey, CA, USA.
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