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Obtaining Diagnostic Classification Model Estimates Using Mplus
Author(s) -
Templin Jonathan,
Hoffman Lesa
Publication year - 2013
Publication title -
educational measurement: issues and practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.158
H-Index - 52
eISSN - 1745-3992
pISSN - 0731-1745
DOI - 10.1111/emip.12010
Subject(s) - computer science , syntax , categorical variable , latent class model , artificial intelligence , machine learning , aka , class (philosophy) , natural language processing , psychology , library science
Diagnostic classification models (aka cognitive or skills diagnosis models) have shown great promise for evaluating mastery on a multidimensional profile of skills as assessed through examinee responses, but continued development and application of these models has been hindered by a lack of readily available software. In this article we demonstrate how diagnostic classification models may be estimated as confirmatory latent class models using Mplus, thus bridging the gap between the technical presentation of these models and their practical use for assessment in research and applied settings. Using a sample English test of three grammatical skills, we describe how diagnostic classification models can be phrased as latent class models within Mplus and how to obtain the syntax and output needed for estimation and interpretation of the model parameters. We also have written a freely available SAS program that can be used to automatically generate the Mplus syntax. We hope this work will ultimately result in greater access to diagnostic classification models throughout the testing community, from researchers to practitioners.

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