Joint and Conditional Estimation for Implicit Models for Tests with Polytomous Item Scores. Research Report. ETS RR-06-03

Autor/in	Haberman, Shelby J.
Titel	Joint and Conditional Estimation for Implicit Models for Tests with Polytomous Item Scores. Research Report. ETS RR-06-03
Quelle	In: ETS Research Report Series, (2006), (42 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2330-8516
Schlagwörter	Computation; Models; Test Items; Scores; Item Response Theory; Maximum Likelihood Statistics; Probability; Reliability + Suchen Sie Ihr Suchwort? Analogiemodell; Test content; Testaufgabe; Item-Response-Theorie; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Reliabilität
Abstract	Multinomial-response models are available that correspond implicitly to tests in which a total score is computed as the sum of polytomous item scores. For these models, joint and conditional estimation may be considered in much the same way as for the Rasch model for right-scored tests. As in the Rasch model, joint estimation is only attractive if both the number of items and the number of examinees are large, while conditional estimation can be employed for a large number of examinees whether or not the number of items is large. In neither case is computation difficult given currently available computers. Large-sample results favor use of conditional estimation, although some use of joint estimation can be contemplated if the number of items is large. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01