Weighting

We help you calculate selection probabilities in the context of complex sample designs to determine design weights. Furthermore, we support you in the calculation of so-called calibration or adjustment weights to reduce the bias of the estimate caused by non-response.

Weighting is a measure used in statistical data analysis to adjust the sample to the population under investigation. This is necessary when

• the potential bias due to different selection probabilities can be avoided or reduced (design weighting),
• the reduction of potential bias due to non-response is aimed at (adjustment weighting or calibration), or
• a subsequent stratification and reduction of variance can be achieved by adjusting to parameters of the population.

A "weight" is thus a multiplicative factor that can be used for any analysis of a survey data set with the aim of obtaining an unbiased or less biased estimator for the population.