MIMIC Methods for Detecting DIF Among Multiple Groups

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A Bayesian MIMIC Model for Testing Non-uniform DIF in Two and Three Groups

Multiple-indicator multiple cause (MIMIC) models have become a popular latent variable method to detect di erential item functioning (DIF) by practitioners. The ease of including groups for DIF testing and the implementation of MIMIC models in structural equation modeling software have helped drive the use of MIMIC models by applied researchers. However, there are several shortcomings within th...

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Evaluation of MIMIC-Model Methods for DIF Testing With Comparison to Two-Group Analysis.

Differential item functioning (DIF) occurs when an item on a test or questionnaire has different measurement properties for 1 group of people versus another, irrespective of mean differences on the construct. This study focuses on the use of multiple-indicator multiple-cause (MIMIC) structural equation models for DIF testing, parameterized as item response models. The accuracy of these methods,...

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Multiple indicators multiple causes (MIMIC) models (Joreskog & Golberger 1975) can be employed in a psychometric context to test for differential item functioning (DIF) between groups on the measurement of a latent variable (Muthén 1989). MIMIC DIF models can be attributed some favorable properties when compared to alternative DIF testing methods (i.e., Item Response Theory-Likelihood Ratio DIF...

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Background During the past few decades, there have been many studies conducted to evaluate the comparative performance of differential item functioning (DIF) methods under various conditions. These conditions, for example, include small and unbalanced sample size between groups (Woods 2009), short tests (Paek and Wilson 2011), various levels of DIF contamination (Finch 2005), multilevel data (F...

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ژورنال

عنوان ژورنال: Applied Psychological Measurement

سال: 2016

ISSN: 0146-6216,1552-3497

DOI: 10.1177/0146621616659738