Literaturnachweis - Detailanzeige
| Autor/inn/en | Ames, Allison J.; Leventhal, Brian C.; Ezike, Nnamdi C. |
|---|---|
| Titel | Monte Carlo Simulation in Item Response Theory Applications Using SAS |
| Quelle | In: Measurement: Interdisciplinary Research and Perspectives, 18 (2020) 2, S.55-74 (20 Seiten)Infoseite zur Zeitschrift
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| Sprache | englisch |
| Dokumenttyp | gedruckt; online; Zeitschriftenaufsatz |
| ISSN | 1536-6367 |
| DOI | 10.1080/15366367.2019.1689762 |
| Schlagwörter | Monte Carlo Methods; Item Response Theory; Simulation; Computer Software; Goodness of Fit; Universities; Probability; Item Analysis; Test Length; Sample Size; Test Items |
| Abstract | Data simulation and Monte Carlo simulation studies are important skills for researchers and practitioners of educational and psychological measurement, but there are few resources on the topic specific to item response theory. Even fewer resources exist on the statistical software techniques to implement simulation studies. This article presents an introduction to the questions that simulation studies can, and cannot answer, along with the primary steps of the simulation study. We primarily focus on the parts of the simulation for which statistical software is used, presenting syntax for simulating 2PL data, and discuss how to extend the basic syntax to more complex models. We focus on SAS software in the article to build upon an existing syntax base, as most universities have SAS licenses. Two small simulations serve as didactic illustrations and to demonstrate parameter recovery of the SAS IRT procedure and an evaluation of the procedure's item-fit options. (As Provided). |
| Anmerkungen | Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals |
| Erfasst von | ERIC (Education Resources Information Center), Washington, DC |
| Update | 2024/1/01 |
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