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Making the Most of What We Have: A Practical Application of Multidimensional Item Response Theory in Test Scoring

Rutgers, The State University of New Jersey

Richard J. Patz

R. J. Patz, Inc

This article proposes a practical method that capitalizes on the availability of information from multiple tests measuring correlated abilities given in a single test administration. By simultaneously estimating different abilities with the use of a hierarchical Bayesian framework, more precise estimates for each ability dimension are obtained. The efficiency of the proposed method is most pronounced when highly correlated abilities are estimated from multiple short tests. Employing Markov chain Monte Carlo techniques allows for straightforward estimation of model parameters.

Key Words: ability estimation • Bayesian estimation • item response theory • Markov chain Monte Carlo • multidimensionality

Journal of Educational and Behavioral Statistics, Vol. 30, No. 3, 295-311 (2005)
DOI: 10.3102/10769986030003295


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