The Effect of Person Misfit on Classification Decisions

Autor/inn/en	Hendrawan, Irene; Glas, Cees A. W.; Meijer, Rob R.
Titel	The Effect of Person Misfit on Classification Decisions
Quelle	In: Applied Psychological Measurement, 29 (2005) 1, S.26-44 (19 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621604270902
Schlagwörter	Probability; Statistics; Test Length; Simulation; Item Response Theory; Bayesian Statistics; Goodness of Fit; Computation; Classification + Suchen Sie Ihr Suchwort? Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Statistik; Simulation program; Simulationsprogramm; Item-Response-Theorie; Classification system; Klassifikation; Klassifikationssystem
Abstract	The effect of person misfit to an item response theory model on a mastery/nonmastery decision was investigated. Furthermore, it was investigated whether the classification precision can be improved by identifying misfitting respondents using person-fit statistics. A simulation study was conducted to investigate the probability of a correct classification using different cutoff points, estimation methods, person-fit statistics, model violations, test lengths, and sample sizes. The effect of the presence of misfitting item score patterns on the item parameter estimates was also taken into account. Results showed that the effect of the presence of misfitting item score patterns on the classification of nonaberrant simulees was generally small (i.e., the classification precision for these simulees did not go down). Furthermore, for simulees classified as nonaberrant using a person-fit statistic, the classification decisions were comparable with the classification decisions for actual nonaberrant simulees. These results were comparable across different person-fit statistics and estimation methods. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10