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Multidimensional Adaptive Testing with a Minimum Error-Variance Criterion

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  • Wim J. van der Linden

Abstract

Adaptive testing under a multidimensional logistic response model is addressed. An algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood estimator of a linear combination of abilities of interest. The criterion results in a closed-form expression that is easy to evaluate. In addition, it is shown how the algorithm can be modified if the interest is in a test with a "simple ability structure". The statistical properties of the adaptive ML estimator are demonstrated for a two-dimensional item pool with several linear combinations of the abilities.

Suggested Citation

  • Wim J. van der Linden, 1999. "Multidimensional Adaptive Testing with a Minimum Error-Variance Criterion," Journal of Educational and Behavioral Statistics, , vol. 24(4), pages 398-412, December.
    • Handle: RePEc:sae:jedbes:v:24:y:1999:i:4:p:398-412
    DOI: 10.3102/10769986024004398
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