An Explanatory Multidimensional Random Item Effects Rating Scale Model

Autor/inn/en	Huang, Sijia; Luo, Jinwen; Cai, Li
Titel	An Explanatory Multidimensional Random Item Effects Rating Scale Model
Quelle	In: Educational and Psychological Measurement, 83 (2023) 6, S.1229-1248 (20 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Huang, Sijia)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/00131644221140906
Schlagwörter	Rating Scales; Item Response Theory; Models; Test Items; Algorithms; Computation + Suchen Sie Ihr Suchwort? Rating-Skala; Item-Response-Theorie; Analogiemodell; Test content; Testaufgabe; Algorithm; Algorithmus
Abstract	Random item effects item response theory (IRT) models, which treat both person and item effects as random, have received much attention for more than a decade. The random item effects approach has several advantages in many practical settings. The present study introduced an explanatory multidimensional random item effects rating scale model. The proposed model was formulated under a novel parameterization of the nominal response model (NRM), and allows for flexible inclusion of person-related and item-related covariates (e.g., person characteristics and item features) to study their impacts on the person and item latent variables. A new variant of the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm designed for latent variable models with crossed random effects was applied to obtain parameter estimates for the proposed model. A preliminary simulation study was conducted to evaluate the performance of the MH-RM algorithm for estimating the proposed model. Results indicated that the model parameters were well recovered. An empirical data set was analyzed to further illustrate the usage of the proposed model. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01