Improvement in detection of differential item functioning using a mixture item response theory model

A.M. Maij - de Meij, H. Kelderman, H. van der Flier

    Research output: Contribution to JournalArticleAcademicpeer-review

    Abstract

    Usually, methods for detection of differential item functioning (DIF) compare the functioning of items across manifest groups. However, the manifest groups with respect to which the items function differentially may not necessarily coincide with the true source of the bias. It is expected that DIF detection under a model that includes a latent DIF variable is more sensitive to this source of bias. In a simulation study, it is shown that a mixture item response theory model, which includes a latent grouping variable, performs better in identifying DIF items than DIF detection methods using manifest variables only. The difference between manifest and latent DIF detection increases as the correlation between the manifest variable and the true source of the DIF becomes smaller. Different sample sizes, relative group sizes, and significance levels are studied. Finally, an empirical example demonstrates the detection of heterogeneity in a minority sample using a latent grouping variable. Manifest and latent DIF detection methods are applied to a Vocabulary test of the General Aptitude Test Battery (GATB). © Taylor & Francis Group, LLC.
    Original languageEnglish
    Pages (from-to)975-999
    JournalMultivariate Behavioral Research
    Volume45
    DOIs
    Publication statusPublished - 2010

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