Who is at risk of what?
If you have calculated the sample size required for an employee survey or an observational study of departmental practices but found that the number of observations required is larger than the number of employees, chances are the error is due to use of approximation formulae. Many of us unknowingly were taught to use approximations that fail to include the finite population correction factor. Depending on the objective of a study and the proportion of a population sampled, it may be necessary to consider this correction factor in order to estimate standard error and sample size accurately.
Birnbaum
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Applied Epidemiology, Sidney, British Columbia, Canada.
D003428:Cross Infection / Q000453:epidemiology*; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D012107:Research Design / Q000592:standards*; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D018401:Sample Size; D012494:Sampling Studies