Editing Sampling bias (section)

==Statistical corrections for a biased sample==
If entire segments of the population are excluded from a sample, then there are no adjustments that can produce estimates that are representative of the entire population. But if some groups are underrepresented and the degree of underrepresentation can be quantified, then sample weights can correct the bias. However, the success of the correction is limited to the selection model chosen. If certain variables are missing the methods used to correct the bias could be inaccurate.<ref>{{Cite journal| vauthors = Cuddeback G, Wilson E, Orme JG, Combs-Orme T |date=2004|title=Detecting and Statistically Correcting Sample Selection Bias|journal=Journal of Social Service Research|volume=30|issue=3|pages=19–33|doi=10.1300/J079v30n03_02|s2cid=11685550}}</ref>

For example, a hypothetical population might include 10 million men and 10 million women. Suppose that a biased sample of 100 patients included 20 men and 80 women. A researcher could correct for this imbalance by [[weighting|attaching a weight]] of 2.5 for each male and 0.625 for each female. This would adjust any estimates to achieve the same expected value as a sample that included exactly 50 men and 50 women, unless men and women differed in their likelihood of taking part in the survey.{{Citation needed|date=April 2022}}