Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables

Autor/inn/en	Henson, Robert A.; Templin, Jonathan L.; Willse, John T.
Titel	Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables
Quelle	In: Psychometrika, 74 (2009) 2, S.191-210 (20 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0033-3123
DOI	10.1007/s11336-008-9089-5
Schlagwörter	Identification; Probability; Item Response Theory; Mastery Tests; Models; Cognitive Processes + Suchen Sie Ihr Suchwort? Identifikation; Identifizierung; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Item-Response-Theorie; Analogiemodell; Cognitive process; Kognitiver Prozess
Abstract	This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for cognitive diagnosis, new alternatives to modeling the functional relationship between attribute mastery and the probability of a correct response are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10