This paper provides a how-to guide for planning, implementing, and evaluating the MIMIC (Multiple Indicator and MultIple Causes) method in diverse populations – in this case, large samples of Black and white respondents from the MADICS study. The MIMIC approach can also probe for differential item functioning (DIF) in longitudinal measures (i.e., temporal invariance). MIMIC models afford powerful claims about measurement – particularly in terms of 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. To increase their use, this tutorial carefully explains how to specify, interpret, and evaluate MIMIC models, as well as provides sample code in R (lavaan) and MPlus. MIMIC models are explained in accessible “plain English” and Greek (notation), with an OSF folder providing annotated code and output.
