ArticleEducational and psychological measurement2022
Detecting Differential Rater Functioning in Severity and Centrality: The Dual DRF Facets Model.
Article in Educational and psychological measurement, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- The Impact of Insufficient Effort Responses on the Order of Category Thresholds in the Polytomous Rasch Model.Educational and psychological measurement · 2024Article
- Human ratings take time: A hierarchical facets model for the joint analysis of ratings and rating times.Behavior research methods · 2024Article
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Authors and funding
2 authors.
Funding
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Abstract
Performance assessments heavily rely on human ratings. These ratings are typically subject to various forms of error and bias, threatening the assessment outcomes' validity and fairness. Differential rater functioning (DRF) is a special kind of threat to fairness manifesting itself in unwanted interactions between raters and performance- or construct-irrelevant factors (e.g., examinee gender, rater experience, or time of rating). Most DRF studies have focused on whether raters show differential severity toward known groups of examinees. This study expands the DRF framework and investigates the more complex case of dual DRF effects, where DRF is simultaneously present in rater severity and centrality. Adopting a facets modeling approach, we propose the dual DRF model (DDRFM) for detecting and measuring these effects. In two simulation studies, we found that dual DRF effects (a) negatively affected measurement quality and (b) can reliably be detected and compensated under the DDRFM. Using sample data from a large-scale writing assessment (
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