this post was submitted on 26 Feb 2024
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chapotraphouse
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The purpose is to measure the effect of a single variable, so you make sure to correct for all other variables. For example, to measure the effect of height you might compare white men only against white men, black women only against black women, etc.
In a study measuring the gender pay gap, they would be correcting for variables other than gender.
Is that what "this estimation assumes other factors associated with earning potential — for instance, gender, age, years of schooling, and location — are held equal," means? Cuz that's not what it sounds like. Assuming things are equal isn't this statistical matching thing you are talking about
Edit: I found the study so I'm trying to figure out how these other factors are controlled for.
Yes. And usually these factors are controlled for when picking your study's sample.
https://www.statisticshowto.com/matched-samples/
"All factors held equal" doesn't mean the different factors are equal in effect, just that the sample is chosen such that the other factors are identical across the two groups.
Yes, that's what it means - if all other factors they list are equal, meaning if the only difference is height.