A Monte Carlo Approach to Unidimensionality Testing in Polytomous Rasch Models

Autor/inn/en	Christensen, Karl Bang; Kreiner, Svend
Titel	A Monte Carlo Approach to Unidimensionality Testing in Polytomous Rasch Models
Quelle	In: Applied Psychological Measurement, 31 (2007) 1, S.20-30 (11 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621605286204
Schlagwörter	Item Response Theory; Monte Carlo Methods; Testing; Models; Sample Size; Statistical Analysis; Maximum Likelihood Statistics; Computation; Correlation; Probability + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Monte-Carlo-Methode; Testdurchführung; Testen; Analogiemodell; Statistische Analyse; Korrelation; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie
Abstract	Many statistical tests are designed to test the different assumptions of the Rasch model, but only few are directed at detecting multidimensionality. The Martin-Lof test is an attractive approach, the disadvantage being that its null distribution deviates strongly from the asymptotic chi-square distribution for most realistic sample sizes. A Monte Carlo test approach to p value computation is proposed and is shown to yield a powerful test. Repeated and sequential Monte Carlo tests that can greatly reduce computing time are discussed. (Contains 2 tables and 2 figures.) (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10