Quantitative critical (QuantCrit) methods seek to apply Critical Race Theory and it’s tenets to quantitative research to better identify and address oppression. At the same time, statisticians and scientists are pointing out problematic practices in the sciences, from the improper use of p-values to unconscious decisions that manipulate research findings. I will discuss ways QuantCrit guides my ongoing equity research, from the way I collect and handle data to how I build and interpret statistical models. To extend this discussion to future work, I will describe how these principles apply to three research projects extending from my current work. 1) Using the experience sampling method to investigate situations where college science courses induce stereotype threat. 2) Moving QuantCrit from theory to practice. 3) Supporting instructors pursuing equity in their courses through a low-stakes, cognitive diagnostic - computerized adaptive test to inform student skill and knowledge development throughout introductory physics courses.