What are the
consequences of a low response rate?
1. Results of statistical analysis
may suffer from “nonresponse bias”.
This typically occurs if those who choose to participate
(respondents) differ substantially in some way from those who choose not to
participate (nonrespondents). If
these differences are related to critical information from the survey or
the census, the results may be misleading or even erroneous.
2. The variance estimate will be
understated. An incomplete sample
fails to capture the full variability that would be observed in a complete
sample.
3. Inaccurate representations of the
underlying distribution - errors in statistics that are sensitive to the
distribution are large at low response rates.
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