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

Published online by Cambridge University Press:  01 January 2025

Robert A. Henson ,
Jonathan L. Templin  and
John T. Willse
Robert A. Henson*
Affiliation:
The University of North Carolina at Greensboro
Jonathan L. Templin
Affiliation:
University of Georgia
John T. Willse
Affiliation:
The University of North Carolina at Greensboro
*
Requests for reprints should be sent to Robert A. Henson, The University of North Carolina at Greensboro, Greensboro, USA. E-mail: [email protected]
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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.

Keywords

cognitive diagnosis modelslog-linear latent class modelslatent class models
Type
Theory and Methods
Information
Psychometrika , Volume 74 , Issue 2 , June 2009 , pp. 191 - 210
Copyright
Copyright © 2008 The Psychometric Society

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