Multidimensional Adaptive Testing with a Minimum Error - Variance Criterion

The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple expression in closed form. In addition, it is shown how the algorithm can be adapted if the interest is in a test with a "simple information structure." The statistical properties of the adaptive ML estimator are demonstrated for a two-dimensional item pool with several linear combinations of the two abilities. (Contains 1 figure and 15 references.) (Author/SLD) ******************************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ******************************************************************************** O o Multidimensional Adaptive Testing Research with a Minimum Error-Variance Criterion Report 97-03 Wim J. van der Linden U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) 0.."document has been reproduced as received from the person or organization originating it. 1:1 Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. BEST COPY AVAILABLE 2 Multidimensional Adaptive Testing with a Minimum Error-Variance Criterion Wim J. van der Linden