Hello everyone,
I was wondering if you all would be able to help me answer a question (or steer me toward potential resources that may help) regarding SES, and how best to delineate low/medium/high SES groupings.
I am setting up a study where I will be using quota sampling as part of my recruitment. This is being done in order to ensure sufficient variation in the full sample to represent observed diversity in SES – across high, medium, and low SES quotas. My main question involves the best way to group individuals into “high” “medium” and “low” SES quotas. While I will be using 2-3 different measures of SES (Hollingshead Index, Subjective Social Status) when running analyses, in order to ensure quotas are being met, my online questionnaire will include survey logic to group participants into low/mid/high SES quotas.
My question is, what established guidelines exist that I can use in my survey logic to help identify low/mid/high SES scores? I understand SES is a complex social construct which can be comprised of several parts, but was wondering if anyone had any ideas for specific cutpoints used to operationalize someone “low in SES.”
Thanks!
you mention that you will be using2-3 meaures to ensure quotas are met - could you clarify what you mean by that?
Also what do you mean by survey logic?
What Robert is seeking here is established classification criteria for "low," "medium," and "high" socioeconomic status categories for adults in the USA, based perhaps on some composite of key SES components such as income + education levels, as a simple/efficient yet valid way to sample to ensure sufficient sample variability in SES (just using convenience sampling of predefined low/med/high SES quotas, vs. trying to obtain nationally representative stratified samples), and then give those sampled more a more comprehensive SES measure (e.g., that might include occupation, wealth, subjective SES). A concern it seems, for instance, with just sampling based on observed national income levels (e.g., lower 1/3, middle 1/3, upper 1/3) is that those who would be classified, say, as "low SES" might not fall into conventional "low SES" categories (e.g., 20-year-old college student who currently earns
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