A comparison of item selection rules at the early stages of computerized adaptive testing

Shu Ying Chen, Robert D. Ankenmann, Hua Hua Chang

Research output: Contribution to journalArticlepeer-review

Abstract

The effects of five item selection rules - Fisher information (FI), Fisher interval information (FII), Fisher information with a posterior distribution (FIP), Kullback-Leibler information (KL), and Kullback-Leibler information with a posterior distribution (KLP) - were compared with respect to the efficiency and precision of trait (θ) estimation at the early stages of computerized adaptive testing (CAT). FII, FIP, KL, and KLP performed marginally better than FI at the early stages of CAT for θ = -3 and -2. For tests longer than 10 items, there appeared to be no precision advantage for any of the selection rules.

Original languageEnglish (US)
Pages (from-to)241-255
Number of pages15
JournalApplied Psychological Measurement
Volume24
Issue number3
DOIs
StatePublished - Sep 2000
Externally publishedYes

Keywords

  • Computerized adaptive testing
  • Fisher information
  • Global information
  • Item information
  • Item response theory
  • Kullback-Leibler information
  • Local information

ASJC Scopus subject areas

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

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