Data Analysis

Be critical of the potential for your positionality to bias the analysis choice and interpretation.

Strive for racial, cultural, and/or linguistic concordance for those analyzing the data, especially for qualitative data.

Include community partners (as defined earlier) in decisions related to and/or conducting of analyses, as well as interpretations of results.

Categorize race/ethnicity by distinct and meaningful groups.

If including measure of racism, consider where racism vs race should be used in analyses.

Disaggregate impacts of social interventions among different racial and ethnic groups.

Explore intersectionality of race and racism with other dimensions of identity that make sense for your research question.

Be intentional about your reference group.

Explore your results through an asset-based lens.

Engage in member checking/community validation: Bring your results to community members (who may or may not have been involved in the research) for their feedback.