Using QuantCrit to Advance an Anti-Racist Developmental Science: Applications to Mixture Modeling

How researchers use statistical analyses shapes their research toward or away from an anti-racist agenda. In this article, we demonstrate how developmental scientists can use the QuantCrit framework to critically examine the process of conducting quantitative analyses. In particular, we focus on mixture modeling to clearly demonstrate how the integration of QuantCrit can be achieved within a statistical technique. We first summarize the tenets of QuantCrit and how it has turned the lens of critical race theory onto quantitative methodology. Second, we provide a summary of the key concepts of mixture modeling. The main section of the article is organized according to three moments that occur in quantitative research: (1) development of the research question(s) and identification of analysis variables; (2) decision-making about the role of race in planned analyses; and (3) interpretation of the results through a theoretical framework. We describe each moment, illustrate how researchers can use QuantCrit principles within it, and offer as examples empirical articles from adolescent research where these strategies have been implemented during mixture modeling. It is our hope that readers will identify moments in their own analyses in which these (and other) principles could be applied.

Automated summary

This article demonstrates how researchers can critically examine the process of conducting quantitative analyses using the QuantCrit framework, focusing on mixture modeling. The research process is organized into three moments, including developing research questions, making decisions about the role of race in analysis, and interpreting results. Researchers can use QuantCrit principles at these moments and learn how these strategies have been implemented through empirical examples.