| Full text | |
| Author(s): |
Total Authors: 4
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| Affiliation: | [1] Univ Sao Paulo, Sao Paulo - Brazil
[2] Univ Fed Sao Carlos, Sao Carlos, SP - Brazil
[3] Univ Calif, Merced, CA - USA
[4] Univ Florida, Gainesville, FL - USA
Total Affiliations: 4
|
| Document type: | Journal article |
| Source: | EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT; v. 79, n. 4, p. 665-687, AUG 2019. |
| Web of Science Citations: | 0 |
| 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. (AU) | |
| FAPESP's process: | 17/15452-5 - New regression models to data set with binary and/or bounded response |
| Grantee: | Jorge Luis Bazan Guzman |
| Support Opportunities: | Scholarships abroad - Research |