A Finite Mixture Item Response Theory Model for Continuous Measurement Outcomes

Autor/in	Zopluoglu, Cengiz
Titel	A Finite Mixture Item Response Theory Model for Continuous Measurement Outcomes
Quelle	In: Educational and Psychological Measurement, 80 (2020) 2, S.346-364 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Zopluoglu, Cengiz)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164419856663
Schlagwörter	Item Response Theory; Measurement; Models; Heuristics; Data Analysis; Monte Carlo Methods; Sample Size + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Messverfahren; Analogiemodell; Heuristik; Auswertung; Monte-Carlo-Methode
Abstract	A mixture extension of Samejima's continuous response model for continuous measurement outcomes and its estimation through a heuristic approach based on limited-information factor analysis is introduced. Using an empirical data set, it is shown that two groups of respondents that differ both qualitatively and quantitatively in their response behavior can be revealed. In addition to the real data application, the effectiveness of the heuristic estimation approach under real data analytic conditions was examined through a Monte Carlo simulation study. The results showed that the heuristic estimation approach provided reliable parameter estimates and the model successfully converged above 80% when the sample size was 250 and above 90% when the sample size was 500 or 1,000 for most conditions. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2022/1/01