A Cognitive Diagnosis Model for Continuous Response

Nathan D. Minchen, Jimmy de la Torre and Ying Liu
Additional contact information
Nathan D. Minchen: Rutgers, The State University of New Jersey
Jimmy de la Torre: The University of Hong Kong
Ying Liu: University of Southern California

Journal of Educational and Behavioral Statistics, 2017, vol. 42, issue 6, 651-677

Abstract: Nondichotomous response models have been of greater interest in recent years due to the increasing use of different scoring methods and various performance measures. As an important alternative to dichotomous scoring, the use of continuous response formats has been found in the literature. To assess finer-grained skills or attributes and to extract information with diagnostic value from continuous response data, a multidimensional skills diagnosis model for continuous response is proposed. An expectation-maximization implementation of marginal maximum likelihood estimation is developed to estimate its parameters. The viability of the proposed model is shown via a simulation study and a real data example. The proposed model is also shown to provide a substantial improvement in attribute classification when compared to a model based on dichotomized continuous responses.

Keywords: cognitive diagnosis models; continuous response; DINA model (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.3102/1076998617703060 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:42:y:2017:i:6:p:651-677

DOI: 10.3102/1076998617703060

Access Statistics for this article

More articles in Journal of Educational and Behavioral Statistics
Bibliographic data for series maintained by SAGE Publications ().