A Stepwise Test Characteristic Curve Method to Detect Item Parameter Drift

Autor/inn/en	Guo, Rui; Zheng, Yi; Chang, Hua-Hua
Titel	A Stepwise Test Characteristic Curve Method to Detect Item Parameter Drift
Quelle	In: Journal of Educational Measurement, 52 (2015) 3, S.280-300 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/jedm.12077
Schlagwörter	Item Response Theory; Test Items; Evaluation Methods; Equated Scores; Simulation; Data Analysis + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Test content; Testaufgabe; Simulation program; Simulationsprogramm; Auswertung
Abstract	An important assumption of item response theory is item parameter invariance. Sometimes, however, item parameters are not invariant across different test administrations due to factors other than sampling error; this phenomenon is termed item parameter drift. Several methods have been developed to detect drifted items. However, most of the existing methods were designed to detect drifts in individual items, which may not be adequate for test characteristic curve-based linking or equating. One example is the item response theory-based true score equating, whose goal is to generate a conversion table to relate number-correct scores on two forms based on their test characteristic curves. This article introduces a stepwise test characteristic curve method to detect item parameter drift iteratively based on test characteristic curves without needing to set any predetermined critical values. Comparisons are made between the proposed method and two existing methods under the three-parameter logistic item response model through simulation and real data analysis. Results show that the proposed method produces a small difference in test characteristic curves between administrations, an accurate conversion table, and a good classification of drifted and nondrifted items and at the same time keeps a large amount of linking items. (As Provided).
Anmerkungen	Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01