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- Publisher Website: 10.3102/10769986231163320
- Scopus: eid_2-s2.0-85153702832
- WOS: WOS:000975521500001
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Article: Latent Transition Cognitive Diagnosis Model With Covariates: A Three-Step Approach
Title | Latent Transition Cognitive Diagnosis Model With Covariates: A Three-Step Approach |
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Authors | |
Keywords | bias-correction cognitive diagnosis models covariates G-DINA model latent transition analysis three-step approach |
Issue Date | 25-Apr-2023 |
Publisher | SAGE Publications |
Citation | Journal of Educational and Behavioral Statistics, 2023, v. 48, n. 6, p. 690-718 How to Cite? |
Abstract | To expand the use of cognitive diagnosis models (CDMs) to longitudinal assessments, this study proposes a bias-corrected three-step estimation approach for latent transition CDMs with covariates by integrating a general CDM and a latent transition model. The proposed method can be used to assess changes in attribute mastery status and attribute profiles and to evaluate the covariate effects on both the initial state and transition probabilities over time using latent (multinomial) logistic regression. Because stepwise approaches generally yield biased estimates, correction for classification error probabilities is considered in this study. The results of the simulation study showed that the proposed method yielded more accurate parameter estimates than the uncorrected approach. The use of the proposed method is also illustrated using a set of real data. |
Persistent Identifier | http://hdl.handle.net/10722/341868 |
ISSN | 2023 Impact Factor: 1.9 2023 SCImago Journal Rankings: 1.336 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Liang, Qianru | - |
dc.contributor.author | de la Torre, Jimmy | - |
dc.contributor.author | Law, Nancy | - |
dc.date.accessioned | 2024-03-26T05:37:48Z | - |
dc.date.available | 2024-03-26T05:37:48Z | - |
dc.date.issued | 2023-04-25 | - |
dc.identifier.citation | Journal of Educational and Behavioral Statistics, 2023, v. 48, n. 6, p. 690-718 | - |
dc.identifier.issn | 1076-9986 | - |
dc.identifier.uri | http://hdl.handle.net/10722/341868 | - |
dc.description.abstract | <p>To expand the use of cognitive diagnosis models (CDMs) to longitudinal assessments, this study proposes a bias-corrected three-step estimation approach for latent transition CDMs with covariates by integrating a general CDM and a latent transition model. The proposed method can be used to assess changes in attribute mastery status and attribute profiles and to evaluate the covariate effects on both the initial state and transition probabilities over time using latent (multinomial) logistic regression. Because stepwise approaches generally yield biased estimates, correction for classification error probabilities is considered in this study. The results of the simulation study showed that the proposed method yielded more accurate parameter estimates than the uncorrected approach. The use of the proposed method is also illustrated using a set of real data.<br></p> | - |
dc.language | eng | - |
dc.publisher | SAGE Publications | - |
dc.relation.ispartof | Journal of Educational and Behavioral Statistics | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | bias-correction | - |
dc.subject | cognitive diagnosis models | - |
dc.subject | covariates | - |
dc.subject | G-DINA model | - |
dc.subject | latent transition analysis | - |
dc.subject | three-step approach | - |
dc.title | Latent Transition Cognitive Diagnosis Model With Covariates: A Three-Step Approach | - |
dc.type | Article | - |
dc.identifier.doi | 10.3102/10769986231163320 | - |
dc.identifier.scopus | eid_2-s2.0-85153702832 | - |
dc.identifier.volume | 48 | - |
dc.identifier.issue | 6 | - |
dc.identifier.spage | 690 | - |
dc.identifier.epage | 718 | - |
dc.identifier.eissn | 1935-1054 | - |
dc.identifier.isi | WOS:000975521500001 | - |
dc.identifier.issnl | 1076-9986 | - |