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

Jimmy de la Torre and Richard J. Patz

Journal of Educational and Behavioral Statistics, 2005, vol. 30, issue 3, 295-311

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.

Keywords: ability estimation; Bayesian estimation; item response theory; Markov chain Monte Carlo; multidimensionality (search for similar items in EconPapers)
Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/10769986030003295 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:30:y:2005:i:3:p:295-311

DOI: 10.3102/10769986030003295

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().