Incorporating the Q-Matrix into Multidimensional Item Response Theory Models

Autor/inn/en	da Silva, Marcelo A.; Liu, Ren; Huggins-Manley, Anne C.; Bazán, Jorge L.
Titel	Incorporating the Q-Matrix into Multidimensional Item Response Theory Models
Quelle	In: Educational and Psychological Measurement, 79 (2019) 4, S.665-687 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (da Silva, Marcelo A.) ORCID (Liu, Ren)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1644
DOI	10.1177/0013164418814898
Schlagwörter	Item Response Theory; Matrices; Models; Bayesian Statistics; Statistical Analysis; Computation; Markov Processes; Monte Carlo Methods + Suchen Sie Ihr Suchwort? Item-Response-Theorie; Matrizenrechnung; Analogiemodell; Statistische Analyse; Markowscher Prozess; Monte-Carlo-Methode
Abstract	Multidimensional item response theory (MIRT) models use data from individual item responses to estimate multiple latent traits of interest, making them useful in educational and psychological measurement, among other areas. When MIRT models are applied in practice, it is not uncommon to see that some items are designed to measure all latent traits while other items may only measure one or two traits. In order to facilitate a clear expression of which items measure which traits and formulate such relationships as a math function in MIRT models, we applied the concept of the Q-matrix commonly used in diagnostic classification models to MIRT models. In this study, we introduced how to incorporate a Q-matrix into an existing MIRT model, and demonstrated benefits of the proposed hybrid model through two simulation studies and an applied study. In addition, we showed the relative ease in modeling educational and psychological data through a Bayesian approach via the NUTS algorithm. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01