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If you've designed your sampling properly, a 75% response rate is more than sufficient. Maybe that was choice C? This isn't really a statistics question per se

If you've designed your sampling properly, a 75% response rate is more than sufficient. Maybe that was choice C? This isn't really a statistics question per se; it's a question about how to design and operate a research survey. Suggesting that you need a 100% response rate is absurd and perpetuates a deep misunderstanding of research design.

tlb 4y ago
My survey shows that 100% of people answer unsolicited phone calls. Before running with missing data, you need to make the case that there's no plausible reason why non-respondents would have different answers from respondents.
- Aeolun 4y ago
  > My survey shows that 100% of people answer unsolicited phone calls. Did you not count all the people that didn’t respond? This is just a problem with inference, not the sampling. “100% of the _respondents_ answer unsolicited phone calls _at least some of the time_”.
  - tlb 4y ago
    Yes, that's the point. People who respond to surveys are different from people who don't. The challenge is: when you ask some question that might be correlated to responsiveness, like "how many hours per week do you work?", you basically end up with zero information about what you care about (how many hours average people work.)
dlkf 4y ago
> If you've designed your sampling properly You are making a much stronger assumption than this. You are assuming access to demographic information of each subject, as well as population base rates for a sufficient set of attributes to correct for non-response bias. Maybe we have that, maybe we don’t. If we don’t, option A is a good tack.
deleted 4y ago
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bloak 4y ago
Where does "75%" come from? If I were trying to estimate what proportion of the population can read, or what proportion of the population is too busy to answer a questionnaire, then I wouldn't assume that the 75% who responded are representative of the whole population. Those are extreme examples but there are lots of things that might be correlated with people's willingness to respond. Perhaps choice C was: Start again with a new random sample of students, but this time offer FREE FOOD to everyone who responds.
- ghaff 4y ago
  Nobody operating a survey of this type assumes they'll get 100% response rate. (Although it is very common to offer something like a gift certificate to N randomly chosen people who answer the survey.)
ouid 4y ago
Without any a priori information about the similarity of the responders and the non-responders, you should assume that the non-responders have colluded to hide the effect from you as much as possible. This is not a random sample anymore. You can still get information out of your sample of that form, but its very bad, and you should only pay attention to it if you can't afford to get anything better.
twobitshifter 4y ago
I mostly agree but on the subject of student life, those judging student life to be poor could be the most likely not to engage with the survey. I would go forward with the data, but the response rate should be discussed in the report.

tlb 4y ago

My survey shows that 100% of people answer unsolicited phone calls. Before running with missing data, you need to make the case that there's no plausible reason why non-respondents would have different answers from respondents.

Aeolun 4y ago
> My survey shows that 100% of people answer unsolicited phone calls. Did you not count all the people that didn’t respond? This is just a problem with inference, not the sampling. “100% of the _respondents_ answer unsolicited phone calls _at least some of the time_”.
- tlb 4y ago
  Yes, that's the point. People who respond to surveys are different from people who don't. The challenge is: when you ask some question that might be correlated to responsiveness, like "how many hours per week do you work?", you basically end up with zero information about what you care about (how many hours average people work.)

dlkf 4y ago

> If you've designed your sampling properly You are making a much stronger assumption than this. You are assuming access to demographic information of each subject, as well as population base rates for a sufficient set of attributes to correct for non-response bias. Maybe we have that, maybe we don’t. If we don’t, option A is a good tack.

deleted 4y ago

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bloak 4y ago

Where does "75%" come from? If I were trying to estimate what proportion of the population can read, or what proportion of the population is too busy to answer a questionnaire, then I wouldn't assume that the 75% who responded are representative of the whole population. Those are extreme examples but there are lots of things that might be correlated with people's willingness to respond. Perhaps choice C was: Start again with a new random sample of students, but this time offer FREE FOOD to everyone who responds.

ghaff 4y ago
Nobody operating a survey of this type assumes they'll get 100% response rate. (Although it is very common to offer something like a gift certificate to N randomly chosen people who answer the survey.)

ouid 4y ago

Without any a priori information about the similarity of the responders and the non-responders, you should assume that the non-responders have colluded to hide the effect from you as much as possible. This is not a random sample anymore. You can still get information out of your sample of that form, but its very bad, and you should only pay attention to it if you can't afford to get anything better.

twobitshifter 4y ago

I mostly agree but on the subject of student life, those judging student life to be poor could be the most likely not to engage with the survey. I would go forward with the data, but the response rate should be discussed in the report.