Characterizing the Latent Classes in a Mixture IRT Model Using DIF

Autor/in	Karadavut, Tugba
Titel	Characterizing the Latent Classes in a Mixture IRT Model Using DIF
Quelle	In: Applied Measurement in Education, 34 (2021) 4, S.301-311 (11 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0895-7347
DOI	10.1080/08957347.2021.1987900
Schlagwörter	Item Response Theory; Models; Test Items; Maximum Likelihood Statistics; Statistical Analysis; Statistical Significance; Effect Size; Test Validity + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Analogiemodell; Test content; Testaufgabe; Statistische Analyse; Testvalidität
Abstract	Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the examinee or the item characteristics conceptually or statistically. In this study, we propose a two-step procedure for characterizing the latent classes. First, a DIF analysis can be conducted to determine the items that function differentially between the latent classes using the latent class membership information. Then, the characteristics of the items with DIF can be further examined to use this information for characterizing the latent classes. We provided an empirical example to illustrate this procedure. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01