Vertical Scaling with the Rasch Model Utilizing Default and Tight Convergence Settings with WINSTEPS and BILOG-MG

Autor/inn/en	Custer, Michael; Omar, Md Hafidz; Pomplun, Mark
Titel	Vertical Scaling with the Rasch Model Utilizing Default and Tight Convergence Settings with WINSTEPS and BILOG-MG
Quelle	In: Applied Measurement in Education, 19 (2006) 2, S.133-149 (17 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0895-7347
DOI	10.1207/s15324818ame1902_4
Schlagwörter	Models; Scaling; Computer Software; Vocabulary; Measures (Individuals); Comparative Analysis; Tests; Simulation; Item Response Theory + Suchen Sie Ihr Suchwort? Analogiemodell; Scale construction; Skalenkonstruktion; Wortschatz; Messdaten; Examination; Prüfung; Examen; Simulation program; Simulationsprogramm; Item-Response-Theorie
Abstract	This study compared vertical scaling results for the Rasch model from BILOG-MG and WINSTEPS. The item and ability parameters for the simulated vocabulary tests were scaled across 11 grades; kindergarten through 10th. Data were based on real data and were simulated under normal and skewed distribution assumptions. WINSTEPS and BILOG-MG were each executed with default and tightened convergence settings. The results were compared in terms of differences and correlations between estimated item and ability parameters. Under default convergence settings, BILOG-MG appeared to capture the individual and mean estimates more accurately. However, once convergence settings were tightened, the programs generated similar results and reproduced the simulated parameter estimates more accurately than when default convergence settings were used. (Author).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10