Latent Transition Cognitive Diagnosis Model with Covariates: A Three-Step Approach

Autor/inn/en	Liang, Qianru; de la Torre, Jimmy; Law, Nancy
Titel	Latent Transition Cognitive Diagnosis Model with Covariates: A Three-Step Approach
Quelle	In: Journal of Educational and Behavioral Statistics, 48 (2023) 6, S.690-718 (29 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Liang, Qianru) ORCID (Law, Nancy)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/10769986231163320
Schlagwörter	Cognitive Measurement; Models; Statistical Bias; Computation; Error Correction; Probability + Suchen Sie Ihr Suchwort? Analogiemodell; Korrektur; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie
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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01