These traits mean the sample is systematically different from the target population, potentially resulting in biased estimates.
Subsequent research published in 1976 and 1988 concluded that non-response bias was the primary source of this error, although their sampling frame was also quite different from the vast majority of voters.
A common technique involves comparing the first and fourth quartiles of responses for differences in demographics and key constructs.
[7][8][9] Some academic journals, particularly in the medical space, require minimum response rates to publish survey research as a means of mitigating non-response bias.
It may also result in gatekeeping of surveys that may be valid on their merits, but fail to satisfy a heuristic requirement on response rates.