Impact of DIF on General Factor Mean Comparisons for Bifactor, Ordinal Data

Autor/inn/en	Liu, Yixing; Thompson, Marilyn S.
Titel	Impact of DIF on General Factor Mean Comparisons for Bifactor, Ordinal Data
Quelle	In: Journal of Experimental Education, 90 (2022) 4, S.981-1002 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0973
DOI	10.1080/00220973.2021.1926895
Schlagwörter	Comparative Analysis; Item Analysis; Sample Size; Error of Measurement; Factor Analysis; Statistical Bias; Psychological Patterns; Monte Carlo Methods; Classification; Item Response Theory + Suchen Sie Ihr Suchwort? Itemanalyse; Messfehler; Faktorenanalyse; Monte-Carlo-Methode; Classification system; Klassifikation; Klassifikationssystem; Item-Response-Theorie
Abstract	A simulation study was conducted to explore the impact of differential item functioning (DIF) on general factor difference estimation for bifactor, ordinal data. Common analysis misspecifications in which the generated bifactor data with DIF were fitted using models with equality constraints on noninvariant item parameters were compared under data generation conditions varying by sample size, number of response categories, effect size of the general factor mean difference, and the position and the magnitude of DIF. Estimation bias in the general factor mean difference resulting from ignoring DIF mainly depended on the type of parameters with DIF. When ignoring DIF in threshold parameters, very substantial estimation bias was produced, and Type I error rates (powers) were inflated for many conditions. In contrast, when ignoring DIF in general factor loadings, a little estimation bias was produced; when ignoring DIF in specific factor loadings, almost no estimation bias was produced. All Type I error rates fell within required limits when DIF was present in factor loadings, and powers were not influenced by ignoring DIF in factor loadings. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01