Testing for Nonuniform Differential Item Functioning With Multiple Indicator Multiple Cause Models

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Measurement Invariance and Differential Item Functioning in Latent Class Analysis With Stepwise Multiple Indicator Multiple Cause Modeling (2017, methodology): “It is possible that future studies might reveal Type I error inflation inherent in this iterative testing sequence (similar to the findings of Woods & Grimm, 2011, for testing nonuniform DIF effects using factor MIMIC modeling).”
An Overview and Practical Guide to IRT Measurement Equivalence Analysis (2015, methodology): “This is similar to the newest developments in CFA ME research that uses multiple indicators multiple causes (MIMIC) models (Woods, 2009; Woods et al., 2012; Woods & Grimm, 2011; Woods, Oltmanns, & Turkheimer, 2009).”
Testing Measurement Invariance Using MIMIC (2012, methodology): “First, MIMIC modeling, developed by Joreskog and Goldberger (1975) and disseminated for measurement invariance testing by Muthén (e.g., 1989), tests uniform measurement noninvariance (Woods & Grimm, 2011).”
The Langer-Improved Wald Test for DIF Testing With Multiple Groups (2013, methodology): “In the future, MIMIC-interaction models (Woods & Grimm, 2011), which test for nonuniform DIF, will likely become more readily estimable, and then a comparison between them and Wald testing will be important.”