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A Group Fit Statistic for the Multilevel Item Response Model

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Title: A Group Fit Statistic for the Multilevel Item Response Model
Language: English
Authors: Yishan Ding (ORCID 0000-0002-4798-1040), Ji Seung Yang, Youngjin Han (ORCID 0000-0002-0780-6272)
Source: Journal of Educational Measurement. 2026 63(1).
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 27
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Descriptors: Hierarchical Linear Modeling, Item Response Theory, Goodness of Fit, Test Wiseness, Behavior Patterns, Error Patterns, Prediction, Cheating, Test Items
DOI: 10.1111/jedm.70024
ISSN: 0022-0655
1745-3984
Abstract: Aberrant behaviors among test-takers in large-scale assessments are often more prevalent within specific groups or testing sites. While various techniques have been developed to detect individual-level test-takers' aberrant behaviors, research in detecting those behaviors at the group level is rare. We propose a group fit statistic l[subscript z][subscript 2] by extending the l[subscript z] statistic to a multilevel item response model. This new statistic demonstrates adequate power and effectively controls the Type I error rate, particularly when true latent variable values are used or when group sizes are large, such as 500. When latent variable estimates are employed, an adjustment to the l[subscript z][subscript 2] based on the posterior predictive checking approach can offer improved control over the Type I error rate.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1501255
Database: ERIC
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  Data: A Group Fit Statistic for the Multilevel Item Response Model
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  Data: <searchLink fieldCode="AR" term="%22Yishan+Ding%22">Yishan Ding</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-4798-1040">0000-0002-4798-1040</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ji+Seung+Yang%22">Ji Seung Yang</searchLink><br /><searchLink fieldCode="AR" term="%22Youngjin+Han%22">Youngjin Han</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-0780-6272">0000-0002-0780-6272</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Educational+Measurement%22"><i>Journal of Educational Measurement</i></searchLink>. 2026 63(1).
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  Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
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  Data: 27
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  Data: <searchLink fieldCode="DE" term="%22Hierarchical+Linear+Modeling%22">Hierarchical Linear Modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Item+Response+Theory%22">Item Response Theory</searchLink><br /><searchLink fieldCode="DE" term="%22Goodness+of+Fit%22">Goodness of Fit</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Wiseness%22">Test Wiseness</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Patterns%22">Behavior Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Error+Patterns%22">Error Patterns</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Cheating%22">Cheating</searchLink><br /><searchLink fieldCode="DE" term="%22Test+Items%22">Test Items</searchLink>
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  Data: 10.1111/jedm.70024
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  Data: Aberrant behaviors among test-takers in large-scale assessments are often more prevalent within specific groups or testing sites. While various techniques have been developed to detect individual-level test-takers' aberrant behaviors, research in detecting those behaviors at the group level is rare. We propose a group fit statistic l[subscript z][subscript 2] by extending the l[subscript z] statistic to a multilevel item response model. This new statistic demonstrates adequate power and effectively controls the Type I error rate, particularly when true latent variable values are used or when group sizes are large, such as 500. When latent variable estimates are employed, an adjustment to the l[subscript z][subscript 2] based on the posterior predictive checking approach can offer improved control over the Type I error rate.
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  Data: 2026
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        Value: 10.1111/jedm.70024
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      – Text: English
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        PageCount: 27
    Subjects:
      – SubjectFull: Hierarchical Linear Modeling
        Type: general
      – SubjectFull: Item Response Theory
        Type: general
      – SubjectFull: Goodness of Fit
        Type: general
      – SubjectFull: Test Wiseness
        Type: general
      – SubjectFull: Behavior Patterns
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      – SubjectFull: Error Patterns
        Type: general
      – SubjectFull: Prediction
        Type: general
      – SubjectFull: Cheating
        Type: general
      – SubjectFull: Test Items
        Type: general
    Titles:
      – TitleFull: A Group Fit Statistic for the Multilevel Item Response Model
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            NameFull: Yishan Ding
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            NameFull: Ji Seung Yang
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            NameFull: Youngjin Han
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              Type: published
              Y: 2026
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