Optimal stratification of item pools in a-stratified computerized adaptive testing

Hua Hua Chang, Wim J. Van der Linden

Research output: Contribution to journalArticlepeer-review


A method based on 0-1 linear programming (LP) is presented to stratify an item pool optimally for use in a-stratified adaptive testing. Because the 0-1 LP model belongs to the subclass of models with a network flow structure, efficient solutions are possible. The method is applied to a previous item pool from the computerized adaptive testing (CAT) version of the Graduate Record Exams (GRE) Quantitative Test. The results indicate that the new method performs well in practical situations. It improves item exposure control, reduces the mean squared error in the θ estimates, and increases test reliability.

Original languageEnglish (US)
Pages (from-to)262-274
Number of pages13
JournalApplied Psychological Measurement
Issue number4
StatePublished - Jul 2003
Externally publishedYes


  • 0-1 linear programming
  • a-stratified adaptive testing
  • Computerized adaptive testing
  • Item pool stratification

ASJC Scopus subject areas

  • Psychology(all)
  • Psychology (miscellaneous)
  • Social Sciences (miscellaneous)


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