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ERIC Number: EJ1322223
Record Type: Journal
Publication Date: 2021
Pages: 11
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0895-7347
EISSN: N/A
Available Date: N/A
Characterizing the Latent Classes in a Mixture IRT Model Using DIF
Karadavut, Tugba
Applied Measurement in Education, v34 n4 p301-311 2021
Mixture IRT models address the heterogeneity in a population by extracting latent classes and allowing item parameters to vary between latent classes. Once the latent classes are extracted, they need to be further examined to be characterized. Some approaches have been adopted in the literature for this purpose. These approaches examine either the examinee or the item characteristics conceptually or statistically. In this study, we propose a two-step procedure for characterizing the latent classes. First, a DIF analysis can be conducted to determine the items that function differentially between the latent classes using the latent class membership information. Then, the characteristics of the items with DIF can be further examined to use this information for characterizing the latent classes. We provided an empirical example to illustrate this procedure.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A