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  • https://doi.org/10.1177/23328584251388032Copy DOI Icon

A Primer on MIMIC Models and Critical Quantitative Methods to Increase Their Use

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Abstract

MIMIC (Multiple Indicator and MultIple Causes) models afford powerful claims about measurement—particularly in identifying biased items—and are relatively simple to specify and test. Therefore, we argue that MIMIC models are sorely underutilized and serve important roles in ensuring sound and fair measurement in educational scholarship. When viewed from the perspective of critical quantitative (CritQuant) methodology, MIMICs hold promise in fostering equity-oriented and anti-racist measurement. The MIMIC strategy, employed from a CritQuant perspective, may also reveal how bias in measurement may lead to underestimating the impacts of racism on educational and related outcomes. To increase their use, this primer aims to explain how to specify and evaluate MIMIC models and provides sample code in R (lavaan) and MPlus. The paper concludes by articulating the advantages and disadvantages of MIMICs, from both CritQuant and technical perspectives, to inform educational research.

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