Multidimensional Computerized Adaptive Testing for Classifying Examinees With Within-Dimensionality

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Abstract

A classification method is presented for adaptive classification testing with a multidimensional item response theory (IRT) model in which items are intended to measure multiple traits, that is, within-dimensionality. The reference composite is used with the sequential probability ratio test (SPRT) to make decisions and decide whether testing can be stopped before reaching the maximum test length. Item-selection methods are provided that maximize the determinant of the information matrix at the cutoff point or at the projected ability estimate. A simulation study illustrates the efficiency and effectiveness of the classification method. Simulations were run with the new item-selection methods, random item selection, and maximization of the determinant of the information matrix at the ability estimate. The study also showed that the SPRT with multidimensional IRT has the same characteristics as the SPRT with unidimensional IRT and results in more accurate classifications than the latter when used for multidimensional data.
Original languageEnglish
Pages (from-to)387-404
JournalApplied psychological measurement
Volume40
Issue number6
DOIs
Publication statusPublished - 2016

Keywords

  • METIS-317606
  • IR-101005

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