IDEAS home Printed from https://ideas.repec.org/a/gam/jstats/v8y2025i2p29-d1641536.html
   My bibliography  Save this article

Bias-Corrected Fixed Item Parameter Calibration, with an Application to PISA Data

Author

Listed:
  • Alexander Robitzsch

    (IPN—Leibniz Institute for Science and Mathematics Education, Olshausenstraße 62, 24118 Kiel, Germany
    Centre for International Student Assessment (ZIB), Olshausenstraße 62, 24118 Kiel, Germany)

Abstract

Fixed item parameter calibration (FIPC) is commonly used to compare groups or countries using an item response theory model with a common set of fixed item parameters. However, FIPC has been shown to produce biased estimates of group means and standard deviations in the presence of random differential item functioning (DIF). To address this, a bias-corrected variant of FIPC, called BCFIPC, is introduced in this article. BCFIPC eliminated the bias of FIPC with only minor efficiency losses in certain simulation conditions, but substantial precision gains in many others, particularly for estimating group standard deviations. Finally, a comparison of both methods using the PISA 2009 dataset revealed relatively large differences in country means and standard deviations.

Suggested Citation

  • Alexander Robitzsch, 2025. "Bias-Corrected Fixed Item Parameter Calibration, with an Application to PISA Data," Stats, MDPI, vol. 8(2), pages 1-29, April.
    • Handle: RePEc:gam:jstats:v:8:y:2025:i:2:p:29-:d:1641536
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2571-905X/8/2/29/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2571-905X/8/2/29/
    Download Restriction: no
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jstats:v:8:y:2025:i:2:p:29-:d:1641536. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.