Estimation of Item Response Theory Parameters in the Presence of Missing Data

Autor/in	Finch, Holmes
Titel	Estimation of Item Response Theory Parameters in the Presence of Missing Data
Quelle	In: Journal of Educational Measurement, 45 (2008) 3, S.225-245 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/j.1745-3984.2008.00062.x
Schlagwörter	Simulation; Item Response Theory; Researchers; Computation; Cognitive Measurement + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Item-Response-Theorie; Researcher; Forscher
Abstract	Missing data are a common problem in a variety of measurement settings, including responses to items on both cognitive and affective assessments. Researchers have shown that such missing data may create problems in the estimation of item difficulty parameters in the Item Response Theory (IRT) context, particularly if they are ignored. At the same time, a number of data imputation methods have been developed outside of the IRT framework and been shown to be effective tools for dealing with missing data. The current study takes several of these methods that have been found to be useful in other contexts and investigates their performance with IRT data that contain missing values. Through a simulation study, it is shown that these methods exhibit varying degrees of effectiveness in terms of imputing data that in turn produce accurate sample estimates of item difficulty and discrimination parameters. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10