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

Author

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  • Jimmy de la Torre
  • Richard J. Patz

Abstract

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.

Suggested Citation

  • Jimmy de la Torre & Richard J. Patz, 2005. "Making the Most of What We Have: A Practical Application of Multidimensional Item Response Theory in Test Scoring," Journal of Educational and Behavioral Statistics, , vol. 30(3), pages 295-311, September.
    • Handle: RePEc:sae:jedbes:v:30:y:2005:i:3:p:295-311
    DOI: 10.3102/10769986030003295
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    Cited by:

    1. Padilla, Juan L. & Azevedo, Caio L.N. & Lachos, Victor H., 2018. "Multidimensional multiple group IRT models with skew normal latent trait distributions," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 250-268.

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