Bayesian or Non-Bayesian: A Comparison Study of Item Parameter Estimation in the Three-Parameter Logistic Model

Autor/inn/en	Gao, Furong; Chen, Lisue
Titel	Bayesian or Non-Bayesian: A Comparison Study of Item Parameter Estimation in the Three-Parameter Logistic Model
Quelle	In: Applied Measurement in Education, 18 (2005) 4, S.351-380 (30 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0895-7347
DOI	10.1207/s15324818ame1804_2
Schlagwörter	Simulation; Computation; Bayesian Statistics; Item Analysis; Statistical Analysis; Evaluation Methods; Maximum Likelihood Statistics + Suchen Sie Ihr Suchwort? Simulation program; Simulationsprogramm; Itemanalyse; Statistische Analyse
Abstract	Through a large-scale simulation study, this article compares item parameter estimates obtained by the marginal maximum likelihood estimation (MMLE) and marginal Bayes modal estimation (MBME) procedures in the 3-parameter logistic model. The impact of different prior specifications on the MBME estimates is also investigated using carefully selected prior distributions. The results indicate that, in general, the MBME provides more accurate item parameter estimates than the MMLE procedure. The impact of different priors on the Bayesian estimates is modest when the examinee sample size is not extremely small. (Author).
Anmerkungen	Lawrence Erlbaum Associates, Inc., Journal Subscription Department, 10 Industrial Avenue, Mahwah, NJ 07430-2262. Tel: 800-926-6579 (Toll Free); e-mail: journals@erlbaum.com.
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10