How can non-response bias affect error estimation and how can error sampling techniques mitigate it?

Non-response bias occurs when individuals selected for the sample don't participate, and those who don't respond differ systematically from those who do. This can significantly inflate the margin of error and lead to inaccurate conclusions. Error sampling techniques, especially stratified sampling, can help mitigate non-response bias. By ensuring representation from different subgroups, even if some subgroups have higher non-response rates, stratified sampling can improve the accuracy of the error estimate. Weighting techniques can also be applied to adjust for known non-response patterns.