Optimal sequential designs for on-line item estimation

Douglas H. Jones, Zhiying Jin

Research output: Contribution to journalArticlepeer-review

33 Scopus citations


Replenishing item pools for on-line ability testing requires innovative and efficient data collection designs. By generating local D-optimal designs for selecting individual examinees, and consistently estimating item parameters in the presence of error in the design points, sequential procedures are efficient for on-line item calibration. The estimating error in the on-line ability values is accounted for with an item parameter estimate studied by Stefanski and Carroll. Locally D-optimal n-point designs are derived using the branch-and-bound algorithm of Welch. In simulations, the overall sequential designs appear to be considerably more efficient than random seeding of items.

Original languageEnglish (US)
Pages (from-to)59-75
Number of pages17
Issue number1
StatePublished - Mar 1994

All Science Journal Classification (ASJC) codes

  • Psychology(all)
  • Applied Mathematics


  • branch-and-bound
  • computerized adaptive test
  • exact n-point D-optimal
  • integer programming
  • item response theory
  • measurement errors model
  • on-line testing
  • sequential design


Dive into the research topics of 'Optimal sequential designs for on-line item estimation'. Together they form a unique fingerprint.

Cite this