Exploiting Auxiliary Information about Items in the Estimation of Rasch Item Difficulty Parameters.

Abstract

Standard procedures for estimating th item parameters in IRT models make no use of auxiliary information about test items, such as their format or content, or the skills they require for solution. This paper describes a framework for exploiting this information, thereby enhancing the precision and stability of item parameter estimates and providing diagnostic information about items' operating characteristics. The principles are illustrated in a context for which a relatively simple approximation is available: empirical Bayes estimation of Rasch item difficulty parameters.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1987
Accession Number
ADA184383

Entities

People

  • Robert J. Mislevy

Organizations

  • Educational Testing Service

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Fields of Study

  • Mathematics

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  • Instructional Design and Training Evaluation.
  • Statistical inference.