Traditional vs Intersectional DIF Analysis: Considerations and a Comparison Using State Testing Data

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  • Author(s): Tony Albano; Brian F. French; Thao Thu Vo
  • Language:
    English
  • Source:
    Applied Measurement in Education. 2024 37(1):57-70.
  • Publication Date:
    2024
  • Document Type:
    Journal Articles
    Reports - Research
  • Additional Information
    • Availability:
      Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
    • Peer Reviewed:
      Y
    • Source:
      14
    • Education Level:
      High Schools
      Secondary Education
      Grade 11
    • Subject Terms:
      Test Items; Item Analysis; Data Use; Standardized Tests; High School Students; Grade 11; Mathematics Tests; Language Arts; Evaluation Methods; Item Response Theory; Testing Programs
    • Accession Number:
      10.1080/08957347.2024.2311935
    • ISSN:
      0895-7347
      1532-4818
    • Abstract:
      Recent research has demonstrated an intersectional approach to the study of differential item functioning (DIF). This approach expands DIF to account for the interactions between what have traditionally been treated as separate grouping variables. In this paper, we compare traditional and intersectional DIF analyses using data from a state testing program (nearly 20,000 students in grade 11, math, science, English language arts). We extend previous research on intersectional DIF by employing field test data (embedded within operational forms) and by comparing methods that were adjusted for an increase in Type I error (Mantel-Haenszel and logistic regression). Intersectional analysis flagged more items for DIF compared with traditional methods, even when controlling for the increased number of statistical tests. We discuss implications for state testing programs and consider how intersectionality can be applied in future DIF research.
    • Abstract:
      As Provided
    • Publication Date:
      2024
    • Accession Number:
      EJ1413677