Timeline for Is it valid to compute survey weights using the distribution of a hypothetical/"imaginary" population?
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18 events
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| Oct 9, 2023 at 6:23 | comment | added | Daniela | jdcrossval: this wasn't an online survey, it was a paper version available at different points of interest, with "interviewers" presenting the questionnaire and clarifying things for respondents if they did not know how to interpret some questions (so to sum up, the questionnaire was self-administered, but with immediate help available on request). Now I think about it, I'm not sure if we can really call it a convenience sample, but anyway that's definitely nonprobability sampling. By the way, thanks for your quite useful answer! I'll update my question if additional info come in. | |
| Oct 9, 2023 at 6:23 | vote | accept | Daniela | ||
| Oct 8, 2023 at 21:00 | comment | added | jdcrossval | I'm guessing the goal is to remove bias, but that should be stated explicitly, and the assumption of 50/50 (or something else) should be justified by the available literature. There is some literature suggesting that males and females voluntarily respond to surveys at different rates, which would mean that the unweighted results could be biased and assigning females a lower proportion may remove some of that bias. Was this an online survey, such that you don't know how many males vs. females viewed the link because gender is only known when the respondent fills out the survey? | |
| Oct 8, 2023 at 19:58 | comment | added | Daniela | Alexis: that's what I'm wondering! The justification I got from him was nothing more than "comparing the sample to a hypothetical scenario where there's a 50%/50% distribution of men and women". But to me, nothing really justifies this hypothetical scenario more than another one, hence my doubts. I shall meet him in a couple of days/weeks, I'll enquire (again) about what he's trying to accomplish, maybe it will clarify things. | |
| Oct 8, 2023 at 19:53 | answer | added | jdcrossval | timeline score: 2 | |
| Oct 8, 2023 at 18:37 | comment | added | Alexis | What does the weighting procedure hope to accomplish? What is the motivation for using it? | |
| Oct 8, 2023 at 15:41 | history | edited | Daniela | CC BY-SA 4.0 |
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| Oct 7, 2023 at 20:28 | comment | added | Daniela | num_39: correct. I agree it's difficult or impossible to make inference from a convenience sample. My worry is that we could try this weighting procedure with many different hypothetical distributions, so why choosing specificallly 50/50%? I have serious doubts about how informative it is (I think there's a risk of involuntarily misleading the stakeholders) , but I'm also wondering if I'm being overcautious here or if I'm missing something. | |
| Oct 7, 2023 at 18:59 | comment | added | num_39 | If it's a convenience sample, there's really no more reason to believe it's 70 / 30 than 50 / 50 is there? | |
| Oct 7, 2023 at 17:56 | history | edited | Daniela | CC BY-SA 4.0 |
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| Oct 7, 2023 at 17:51 | comment | added | Daniela | Hi Alexis, thanks for the feedback. The population is comprised of tourists in the small towns of a quite touristy area in a European country (about 30 millions of tourists per year in this area). Unfortunately even data about tourists in general in the country offer no data relative to gender (or other socio-economic characteristics for that matter, barring country of origin). Even if such data was available, I'd be wary about treating tourists in small towns of this area as being like tourists in general (they might even differ from tourists in larger cities in the same area!). | |
| Oct 7, 2023 at 16:50 | comment | added | Alexis | 2/2 What population is the sample trying to represent? Also: Welcome, Daniela! | |
| Oct 7, 2023 at 16:50 | comment | added | Alexis | 1/2 More context is needed to address 'validity'. For example, is the sample from the general population in our species? If so 50/50 (or 51/49, since there are many sexed and gendered selection processes which favor life expectancy among females) might be reasonable. However, if the sample is from, say, a profession with strong gender roles or selection processes (e.g., nursing, public health professional, soldier, etc. depending on country and era), then your suggestion of 40/60 (or 60/40, or some other proportion) might be a more valid assumption of the population generating your sample. | |
| Oct 7, 2023 at 16:45 | history | edited | Alexis | CC BY-SA 4.0 |
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| Oct 7, 2023 at 16:31 | history | edited | Daniela | CC BY-SA 4.0 |
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| Oct 7, 2023 at 6:02 | history | edited | Daniela | CC BY-SA 4.0 |
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| S Oct 7, 2023 at 6:00 | review | First questions | |||
| Oct 7, 2023 at 9:15 | |||||
| S Oct 7, 2023 at 6:00 | history | asked | Daniela | CC BY-SA 4.0 |