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A Group Fit Statistic for the Multilevel Item Response Model

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