One need not look far for an example of epidemiologic research where Indigenous people have either been excluded from analyses or have been aggregated with other racial and ethnic identities as an "Other." Exclusion and aggregation of Indigenous peoples prevents us from adequately characterizing their health in ways that are useful for collective action. In this commentary we describe three distinct, yet related, issues underlying the relationships between statistical power ($/beta /Big)$ and structural and ideational power related to the "small sample size" problem for Indigenous peoples: (i) inadequate data procurement and management processes, (ii) normative methodological practices, and (iii) insufficient scientific communication. In the spirit of disciplinary reflection and self-critique, we identify and review the manifestation of these issues in one author's previously published research. We then discuss and reemphasize important contributing historical and contemporary systems of injustice, and, finally, summarize existing promising research and analytic practices. Given that the tools that address the health of numerically large groups dominate teaching and research spaces, we must move towards a paradigm shift to fully provide equity, justice, and beneficence to Indigenous peoples and other "numerically small" groups.
Keywords: indigenous; power; sample size; statistics.
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