Poststratifikációt

Poststratifikációt is a statistical technique used to adjust survey data to match known population totals for certain demographic or categorical variables. It is often employed when the sample distribution of these variables differs from the known distribution in the population. The primary goal is to improve the accuracy and representativeness of survey estimates, especially when dealing with non-response or sampling biases.

The process typically involves identifying key demographic categories (e.g., age groups, gender, race, education level) for which external, reliable population totals are available. The survey sample is then divided into these same categories, forming strata. Weights are calculated for each stratum based on the ratio of the population total for that stratum to the sample total for that stratum. These weights are then applied to the sample data to adjust the estimates.

Poststratification is a form of weighting that is applied after the data has been collected. It differs from pre-stratification, where the sampling frame is divided into strata before sampling occurs. This method is particularly useful for correcting biases that may arise from differential non-response, where certain subgroups are more or less likely to participate in the survey. By adjusting the sample counts to match known population figures, poststratification helps ensure that the survey results are more generalizable to the target population. It is a widely used technique in survey research and is considered a standard method for improving the reliability of survey estimates.