Multi-Group Generalizations of SIBTEST and Crossing-SIBTEST

Autor/inn/en	Chalmers, R. Philip; Zheng, Guoguo
Titel	Multi-Group Generalizations of SIBTEST and Crossing-SIBTEST
Quelle	In: Applied Measurement in Education, 36 (2023) 2, S.171-191 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Chalmers, R. Philip)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0895-7347
DOI	10.1080/08957347.2023.2201703
Schlagwörter	Test Bias; Test Items; Item Response Theory; Error of Measurement; Monte Carlo Methods; Regression (Statistics); Generalization + Suchen Sie Ihr Suchwort? Testkritik; Test content; Testaufgabe; Item-Response-Theorie; Messfehler; Monte-Carlo-Methode; Regression; Regressionsanalyse
Abstract	This article presents generalizations of SIBTEST and crossing-SIBTEST statistics for differential item functioning (DIF) investigations involving more than two groups. After reviewing the original two-group setup for these statistics, a set of multigroup generalizations that support contrast matrices for joint tests of DIF are presented. To investigate the Type I error and power behavior of these generalizations, a Monte Carlo simulation study was then explored. Results indicated that the proposed generalizations are reasonably effective at recovering their respective population parameter definitions, maintain optimal Type I error control, have suitable power to detect uniform and non-uniform DIF, and in shorter tests are competitive with the generalized logistic regression and generalized Mantel-Haenszel tests for DIF. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01