Weighted Maximum-a-Posteriori Estimation in Tests Composed of Dichotomous and Polytomous Items

Autor/inn/en	Sun, Shan-Shan; Tao, Jian; Chang, Hua-Hua; Shi, Ning-Zhong
Titel	Weighted Maximum-a-Posteriori Estimation in Tests Composed of Dichotomous and Polytomous Items
Quelle	In: Applied Psychological Measurement, 36 (2012) 4, S.271-290 (20 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621612446937
Schlagwörter	Monte Carlo Methods; Computation; Item Response Theory; Weighted Scores; Models; Test Items; Bayesian Statistics; Statistical Bias + Suchen Sie Ihr Suchwort? Monte-Carlo-Methode; Item-Response-Theorie; Analogiemodell; Test content; Testaufgabe
Abstract	For mixed-type tests composed of dichotomous and polytomous items, polytomous items often yield more information than dichotomous items. To reflect the difference between the two types of items and to improve the precision of ability estimation, an adaptive weighted maximum-a-posteriori (WMAP) estimation is proposed. To evaluate the performance of WMAP, a Monte Carlo simulation comparison is presented with maximum likelihood estimation, maximum-a-posteriori estimation, and Jeffreys modal estimation. Simulation results show that the proposed method is much less biased than any of the other estimators, with relatively smaller standard errors and root mean square errors. (Contains 9 figures and 3 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10