An Extension of Four IRT Linking Methods for Mixed-Format Tests

Autor/inn/en	Kim, Seonghoon; Lee, Won-Chan
Titel	An Extension of Four IRT Linking Methods for Mixed-Format Tests
Quelle	In: Journal of Educational Measurement, 43 (2006) 1, S.53-76 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/j.1745-3984.2006.00004.x
Schlagwörter	Simulation; Item Response Theory; Test Format; Measures (Individuals); Multiple Choice Tests + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Item-Response-Theorie; Testentwicklung; Messdaten; Multiple choice examinations; Multiple-choice tests, Multiple-choice examinations; Multiple-Choice-Verfahren
Abstract	Under item response theory (IRT), linking proficiency scales from separate calibrations of multiple forms of a test to achieve a common scale is required in many applications. Four IRT linking methods including the mean/mean, mean/sigma, Haebara, and Stocking-Lord methods have been presented for use with single-format tests. This study extends the four linking methods to a mixture of unidimensional IRT models for mixed-format tests. Each linking method extended is intended to handle mixed-format tests using any mixture of the following five IRT models: the three-parameter logistic, graded response, generalized partial credit, nominal response (NR), and multiple-choice (MC) models. A simulation study is conducted to investigate the performance of the four linking methods extended to mixed-format tests. Overall, the Haebara and Stocking-Lord methods yield more accurate linking results than the mean/mean and mean/sigma methods. When the NR model or the MC model is used to analyze data from mixed-format tests, limitations of the mean/mean, mean/sigma, and Stocking-Lord methods are described. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10