The emerging Critical Quantitative (Crit Quant) perspective is anchored by five guiding principles (i.e., foundation, goals, parity, subjectivity, and self-reflexivity) to mitigate racism and advance social justice. Within this broader methodological perspective, sound measurement is foundational to the quantitative enterprise. Despite the problematic history of measurement, it can be repurposed for critical and equitable ends. MIMIC (Multiple Indicator and Multiple Causes) models are a measurement strategy to simply and efficiently test whether a measure means the same thing and can be measured in the same way across groups (e.g., racial/ethnic and/or gender groups). This talk considers the affordances and limitations of MIMICs for critical quantitative methods, by detecting and mitigating racial, ethnic, gendered, and other forms of bias in items and in measures. Discussion topics will include the affordances of Crit Quant vs QuantCRiT (Quantitative Critical Race Theory) and how Crit Quant and MIMICs do (and don't) detect racism in psychological and social science measures.