View in EDS HTML Full Text PDF Full Text

IRT linking methods for the bifactor model with mixed format tests.

Saved in:
Bibliographic Details
Title: IRT linking methods for the bifactor model with mixed format tests.
Authors: Kim, Sohee (AUTHOR), Cole, Ki Lynn (AUTHOR)
Source: International Journal of Testing. Apr-Jun2025, Vol. 25 Issue 2, p158-177. 20p.
Subjects: Item response theory, Standard deviations, Calibration
Abstract: This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of two methods that incorporated linking coefficients, namely extensions of Haebara and Stocking-Lord, and two methods that did not involve linking coefficients, specifically concurrent calibration and fixed item parameter calibration (FIPC). The study involved an evaluation of the linked item parameters, with a focus on their bias, standard error of estimate (SEE), and root mean squared error (RMSE). The findings revealed that both linking methods, those with and without linking coefficients, demonstrated proficient recovery of item parameters. Notably, the methods lacking linking coefficients exhibited superior performance compared to their counterparts with coefficients. Remarkably, the FIPC linking method emerged as particularly adept at recovering item parameters, especially with regard to difficulty parameters, within the context of the bifactor model. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Testing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: pbh
DbLabel: Psychology and Behavioral Sciences Collection
An: 184711224
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: IRT linking methods for the bifactor model with mixed format tests.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Kim%2C+Sohee%22">Kim, Sohee</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cole%2C+Ki+Lynn%22">Cole, Ki Lynn</searchLink> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Testing%22">International Journal of Testing</searchLink>. Apr-Jun2025, Vol. 25 Issue 2, p158-177. 20p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Item+response+theory%22">Item response theory</searchLink><br /><searchLink fieldCode="DE" term="%22Standard+deviations%22">Standard deviations</searchLink><br /><searchLink fieldCode="DE" term="%22Calibration%22">Calibration</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study conducted a comprehensive comparison of Item Response Theory (IRT) linking methods applied to a bifactor model, examining their performance on both multiple choice (MC) and mixed format tests within the common item nonequivalent group design framework. Four distinct multidimensional IRT linking approaches were explored, consisting of two methods that incorporated linking coefficients, namely extensions of Haebara and Stocking-Lord, and two methods that did not involve linking coefficients, specifically concurrent calibration and fixed item parameter calibration (FIPC). The study involved an evaluation of the linked item parameters, with a focus on their bias, standard error of estimate (SEE), and root mean squared error (RMSE). The findings revealed that both linking methods, those with and without linking coefficients, demonstrated proficient recovery of item parameters. Notably, the methods lacking linking coefficients exhibited superior performance compared to their counterparts with coefficients. Remarkably, the FIPC linking method emerged as particularly adept at recovering item parameters, especially with regard to difficulty parameters, within the context of the bifactor model. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Testing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=184711224
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/15305058.2025.2471752
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 20
        StartPage: 158
    Subjects:
      – SubjectFull: Item response theory
        Type: general
      – SubjectFull: Standard deviations
        Type: general
      – SubjectFull: Calibration
        Type: general
    Titles:
      – TitleFull: IRT linking methods for the bifactor model with mixed format tests.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Kim, Sohee
      – PersonEntity:
          Name:
            NameFull: Cole, Ki Lynn
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Text: Apr-Jun2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 15305058
          Numbering:
            – Type: volume
              Value: 25
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: International Journal of Testing
              Type: main
ResultId 1