Item Response Models for Local Dependence among Multiple Ratings

Autor/inn/en	Wang, Wen-Chung; Su, Chi-Ming; Qiu, Xue-Lan
Titel	Item Response Models for Local Dependence among Multiple Ratings
Quelle	In: Journal of Educational Measurement, 51 (2014) 3, S.260-280 (21 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/jedm.12045
Schlagwörter	Item Response Theory; Interrater Reliability; Models; Correlation; Evaluators + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Interrater-Reliabilität; Analogiemodell; Korrelation
Abstract	Ratings given to the same item response may have a stronger correlation than those given to different item responses, especially when raters interact with one another before giving ratings. The rater bundle model was developed to account for such local dependence by forming multiple ratings given to an item response as a bundle and assigning fixed-effect parameters to describe response patterns in the bundle. Unfortunately, this model becomes difficult to manage when a polytomous item is graded by more than two raters. In this study, by adding random-effect parameters to the facets model, we propose a class of generalized rater models to account for the local dependence among multiple ratings and intrarater variation in severity. A series of simulations was conducted with the freeware WinBUGS to evaluate parameter recovery of the new models and consequences of ignoring the local dependence or intrarater variation in severity. The results revealed a good parameter recovery when the data-generating models were fit, and a poor estimation of parameters and test reliability when the local dependence or intrarater variation in severity was ignored. An empirical example is provided. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10