Multidimensional Adaptive Testing with a Minimum Error-Variance Criterion

Wim J. van der Linden

Journal of Educational and Behavioral Statistics, 1999, vol. 24, issue 4, 398-412

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.

Keywords: Adaptive Testing; Item Response Theory; Maximum-Likelihood Estimation; Multidimensionality (search for similar items in EconPapers)
Date: 1999
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:24:y:1999:i:4:p:398-412

DOI: 10.3102/10769986024004398

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