We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
A General Mixture Model for Cognitive Diagnosis.
- Authors
Olea, Joemari; Santos, Kevin Carl
- Abstract
Although the generalized deterministic inputs, noisy "and" gate model (G-DINA; de la Torre, 2011) is a general cognitive diagnosis model (CDM), it does not account for the heterogeneity that is rooted from the existing latent groups in the population of examinees. To address this, this study proposes the mixture G-DINA model, a CDM that incorporates the G-DINA model within the finite mixture modeling framework. An expectation–maximization algorithm is developed to estimate the mixture G-DINA model. To determine the viability of the proposed model, an extensive simulation study is conducted to examine the parameter recovery performance, model fit, and correct classification rates. Responses to a reading comprehension assessment were analyzed to further demonstrate the capability of the proposed model.
- Subjects
EXPECTATION-maximization algorithms; READING comprehension; DIAGNOSIS
- Publication
Journal of Educational & Behavioral Statistics, 2024, Vol 49, Issue 2, p268
- ISSN
1076-9986
- Publication type
Article
- DOI
10.3102/10769986231176012