Inverse probability weighting.

Statistical analysis usually treats all observations as equally important. In some circumstances, however, it is appropriate to vary the weight given to different observations. Well known examples are in meta-analysis, where the inverse variance (precision) weight given to each contributing study varies, and in the analysis of clustered data. Differential weighting is also used when different parts of the population are sampled with unequal probabilities of selection. Two examples of intentional unbalanced sampling are: 1.Surveys with unequal probabilities of selection—In a national survey of hypertension prevalence, certain groups with relatively rare characteristics (such as people aged ≥65 years) were oversampled to improve the precision of estimates for those groups.