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Detecting differential rater functioning over time (DRIFT) using a Rasch multi-faceted rating scale model.

E W Wolfe1, B C Moulder, C M Myford

  • 1Michigan State University, East Lansing 48840, USA. wolfee@msu.edu

Journal of Applied Measurement
|May 16, 2002
PubMed
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This study introduces Differential Rater Functioning Over Time (DRIFT), identifying rater-by-time interactions. Rasch measurement procedures effectively detect DRIFT, classifying raters, especially for primacy, recency, and centrality effects.

Area of Science:

  • Psychometrics
  • Educational Measurement
  • Rater Behavior Analysis

Background:

  • Rater variability is a significant concern in assessment.
  • Rater effects can change over time, impacting data reliability.
  • Existing methods may not fully capture dynamic rater behaviors.

Purpose of the Study:

  • To introduce and define Differential Rater Functioning Over Time (DRIFT).
  • To present Rasch measurement procedures for identifying DRIFT.
  • To evaluate the effectiveness of these procedures in simulated data.

Main Methods:

  • Development of Rasch measurement models to detect rater-by-time interactions.
  • Simulation of rating data with various DRIFT effects (primacy/recency, centrality/extremism, practice/fatigue).

Related Experiment Videos

  • Application of proposed procedures to classify aberrant raters.

    • Main Results:

    • Procedures effectively classified raters for primacy, recency, and differential centrality/extremism with moderate to large effect sizes.
    • Classification accuracy for practice and fatigue effects was lower.
    • Statistical power for practice/fatigue effects was limited, requiring very large effect sizes.

    Conclusions:

    • Rasch-based methods can identify specific types of DRIFT, improving rater assessment.
    • The procedures show promise for detecting dynamic rater effects in assessment data.
    • Further research may be needed to enhance detection of practice/fatigue effects.