Incorporating the Q-Matrix Into Multidimensional Item Response Theory Models.

Autor: da Silva MA; University of São Paulo, São Paulo, Brazil.; Federal University of São Carlos, São Carlos, Brazil., Liu R; University of California, Merced, CA, USA., Huggins-Manley AC; University of Florida, Gainesville, FL, USA., Bazán JL; University of São Paulo, São Paulo, Brazil.
Jazyk: angličtina
Zdroj: Educational and psychological measurement [Educ Psychol Meas] 2019 Aug; Vol. 79 (4), pp. 665-687. Date of Electronic Publication: 2018 Nov 30.
DOI: 10.1177/0013164418814898
Abstrakt: 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.
Competing Interests: Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
(© The Author(s) 2018.)
Databáze: MEDLINE