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Optimal Designs for Linear Logistic Test Models

  • Ulrike Graßhoff
  • Heinz Holling
  • Rainer Schwabe
Conference paper
Part of the Contributions to Statistics book series (CONTRIB.STAT.)

Abstract

An important class of models within item response theory are Linear Logistic Test Models (LLTM). These models provide a means for rule-based item generation in educational and psychological testing based upon cognitive theories. After a short introduction into the LLTM, optimal designs for the LLTM will be developed with respect to the item calibration step assuming that persons’ abilities are known. Therefore, the LLTM is embedded in a particular generalized linear model. Finally, future developments are outlined.

Keywords

Item Response Theory Item Parameter Item Response Theory Model Adaptive Testing Person Parameter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

Acknowledgements

This research was supported by the Deutsche Forschungsgemeinschaft (DFG) under grant HO 1286/6-1.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Ulrike Graßhoff
    • 1
  • Heinz Holling
    • 2
  • Rainer Schwabe
    • 1
  1. 1.Institut för Mathematische StochastikOtto-von-Guericke-Universität MagdeburgMagdeburgGermany
  2. 2.Psychologisches Institut IVWestfälische Wilhelms-Universität MönsterMönsterGermany

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