A Comparative Study of Test Data Dimensionality Assessment Procedures Under Nonparametric IRT Models

Autor/inn/en	van Abswoude, Alexandra A. H.; van der Ark, L. Andries; Sijtsma, Klaas
Titel	A Comparative Study of Test Data Dimensionality Assessment Procedures Under Nonparametric IRT Models
Quelle	In: Applied Psychological Measurement, 28 (2004) 1, S.3-24 (22 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621603259277
Schlagwörter	Comparative Analysis; Computer Software; Simulation; Nonparametric Statistics; Item Response Theory; Correlation; Factor Analysis + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Item-Response-Theorie; Korrelation; Faktorenanalyse
Abstract	In this article, an overview of nonparametric item response theory methods for determining the dimensionality of item response data is provided. Four methods were considered: MSP, DETECT, HCA/CCPROX, and DIMTEST. First, the methods were compared theoretically. Second, a simulation study was done to compare the effectiveness of MSP, DETECT, and HCA/CCPROX using the default settings of each program in finding a simulated dimensional structure of a matrix of item response data. In several design cells, the methods that use covariances conditional on the latent trait (DETECT and HCA/CCPROX) were superior in finding the simulated structure to the method that used normed unconditional covariances (MSP). Third, the correctness of the decision of accepting or rejecting unidimensionality based on the statistics used in DETECT and DIMTEST was considered. This decision did not always reflect the true dimensionality of the item pool. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10