As social epidemiologists, we use epidemiologic methods to study racism within structures such as housing, education, and the criminal legal system.
But we also need to examine racism within structures in our own field.
But we also need to examine racism within structures in our own field.
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Rules of thumb for sample sizes assume the goal is multivariable models. Descriptive epi is essential to address health inequities.
And exposures more common among marginalized groups are in earlier stages of research.
This encourages transparency.
Many papers report race/ethnicity data in a way that the reader cannot assess whether it was justifiable to exclude or combine racial/ethnic groups.
In situation when sample sizes from marginalized groups are too small to analyze with bivariates or regression models, thoughtfully consider who else is similar enough to be categorized together.
In isolation, imprecise estimates might not be convincing, but if several publications produce similar estimates, we essentially increase the sample size and make progress toward precision.
An “other” estimate is just a weighted average, weighted toward whichever remaining group happens to be the largest in that particular dataset – a group which is rarely identified.