An Algorithm for Testing Unidimensionality and Clustering Items in Rasch Measurement

Autor/inn/en	Debelak, Rudolf; Arendasy, Martin
Titel	An Algorithm for Testing Unidimensionality and Clustering Items in Rasch Measurement
Quelle	In: Educational and Psychological Measurement, 72 (2012) 3, S.375-387 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164411426005
Schlagwörter	Test Items; Factor Analysis; Evaluation Methods; Simulation; Goodness of Fit; Statistical Analysis; Evaluation Research + Suchen Sie Ihr Suchwort? Test content; Testaufgabe; Faktorenanalyse; Simulation program; Simulationsprogramm; Statistische Analyse; Evaluationsforschung
Abstract	A new approach to identify item clusters fitting the Rasch model is described and evaluated using simulated and real data. The proposed method is based on hierarchical cluster analysis and constructs clusters of items that show a good fit to the Rasch model. It thus gives an estimate of the number of independent scales satisfying the postulates of sufficiency of total number of correctly answered items for a person's proficiency, unidimensionality, and local independence that can be constructed from an item set. The method is also compared with the application of a principal components analysis based on tetrachoric correlations. In general, the proposed method was shown to provide practically usable results especially for large person samples. (Contains 2 tables and 1 note.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10