The Asymptotic Distribution of Ability Estimates: Beyond Dichotomous Items and Unidimensional IRT Models

Autor/in	Sinharay, Sandip
Titel	The Asymptotic Distribution of Ability Estimates: Beyond Dichotomous Items and Unidimensional IRT Models
Quelle	In: Journal of Educational and Behavioral Statistics, 40 (2015) 5, S.511-528 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998615606115
Schlagwörter	Item Response Theory; Maximum Likelihood Statistics; Test Items; Ability; Computation + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Test content; Testaufgabe; Fähigkeit; Fertigkeit
Abstract	The maximum likelihood estimate (MLE) of the ability parameter of an item response theory model with known item parameters was proved to be asymptotically normally distributed under a set of regularity conditions for tests involving dichotomous items and a unidimensional ability parameter (Klauer, 1990; Lord, 1983). This article first considers the more general case of tests that include a mix of dichotomous and polytomous items. A proof is given of the asymptotic normality of the MLE of the ability parameter for such tests under a set of regularity conditions. Then, it is proved that a similar result holds for the weighted likelihood estimate and the posterior mode of the ability parameter. Multidimensional ability parameters are considered next. Numerical illustrations are provided to demonstrate the asymptotic results. (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01