Applications of Mixture IRT Models: A Literature Review

Autor/inn/en	Sen, Sedat; Cohen, Allan S.
Titel	Applications of Mixture IRT Models: A Literature Review
Quelle	In: Measurement: Interdisciplinary Research and Perspectives, 17 (2019) 4, S.177-191 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Sen, Sedat) ORCID (Cohen, Allan S.)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-6367
DOI	10.1080/15366367.2019.1583506
Schlagwörter	Item Response Theory; Models; Item Analysis; Personality Traits; Identification; Goodness of Fit; Evaluation Criteria; Sample Size + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Analogiemodell; Itemanalyse; Individual characteristics; Personality characteristic; Persönlichkeitsmerkmal; Identifikation; Identifizierung
Abstract	Mixture item response theory (MixIRT) models combine IRT models with latent class model and assume that there exist latent subpopulations in the data. Identification of latent subpopulations via MixIRT models produces more detailed information. Detailed information about the response processing of examinees provides a better understanding of the construct being measured by the test. These features have enabled the MixIRT models to be used in many studies. Applications of MixIRT models have included item analysis, differential item functioning, multilevel analyses, detection of test speededness, identification of different personality styles and solution strategies. We reviewed each of these applications along with other MixIRT model applications in this study. Results showed reporting practices and trends in MixIRT applications. We provided possible explanations for these results and suggested how to advance the application and usage of MixIRT models. (As Provided).
Anmerkungen	Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01