KNOWLEDGE NETWORKS PROBABILITY-BASED SAMPLING APPROACH FOR SELECTING SAMPLES FROM KNOWLEDGEPANELSM

Brief Description

In September 2007, Knowledge Networks was assigned a U.S. Patent for its unique methodology for selecting online survey samples. The selection methodology, which has been used by KN since 2000, assures that KN panel samples will closely track the U.S. population.

The selection methodology was developed by KN in recognition of the practical issue that different surveys target different subpopulations. Often only panel members with certain characteristics are selected for a survey. This can skew the remaining panel sample and affect the sample representativeness of later surveys.

In our patented solution, a survey assignment method uses a weighting factor to compensate for members which are temporarily removed from a panel because of an earlier draw of sample. This weighting factor adjusts the selection probabilities of the remaining panel members. The solution allows for representative samples to be drawn from the panel, even when earlier surveys oversampled different subpopulations.

For instance, suppose Study A requires a 100% oversample of Hispanics from the panel. At the beginning of the time period, each panel member will have an original selection weight making the panel selection distributions match the demographic benchmarks from the U.S. Census. After the sample draw for Study A is made, the new and temporary selection weights are calculated making the panel selection distributions match the demographics of the general public. Consequently, the sample draw for Study B will yield a representative sample. Each demographic category in the remaining panel is monitored to assure that there are enough members in each category to produce representative survey samples. The process is repeated for each study.

Please see our press announcement or the U.S. Patent for more information.