Observed-score equating as a test assembly problem

Wim J. van der Linden, Richard M. Luecht

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)

Abstract

A set of linear conditions on item response functions is derived that guarantees identical observed-score distributions on two test forms. The conditions can be added as constraints to a linear programming model for test assembly that assembles a new test form to have an observed-score distribution optimally equated to the distribution on an old form. For a well-designed item pool and items fitting the IRT model, use of the model results into observed-score pre-equating and prevents the necessity ofpost hoc equating by a conventional observed-score equating method. An empirical example illustrates the use of the model for an item pool from the Law School Admission Test.
Original languageEnglish
Pages (from-to)401-418
Number of pages17
JournalPsychometrika
Volume63
Issue number4
DOIs
Publication statusPublished - 1998

Keywords

  • Item response theory (IRT)
  • Test equating
  • Test assembly
  • generalized binomial distribution
  • 0–1 linear programming

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