Applying Causal Analysis to Equity Assessments

By Saimun Habib , Mary Munro , Joshua Stadlan , Lilly Boyer , Tamey Habtu

A causal inference-based framing applied to program social equity assessments integrates quantitative evidence and lived experience to identify root causes of disparities in program outcomes and provides data-supported pathways to mitigate them.

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Revisiting studies of racial disparities in NIH grant award rates, we apply a causal analysis framing to conduct social equity assessments of programs and design interventions. Our framing integrates quantitative data and lived experience to identify the root causes of program disparities and provides a data-supported pathway to rectifying them.

Through our case study, we introduce cfairer, a MITRE Independent Research & Development Program-sponsored R package to support causal analysis of unfairness in program data.