2010–11 MacroMonitor Survey Weighting Procedures

Questionnaire Design

The MacroMonitor target for weighting to the national household population in the U.S. is economic household units—a definition that allows households to have more than one economic unit. The U.S. Bureau of the Census defines households as persons sharing a common dwelling unit. The MacroMonitor definition of economic household includes families, individuals living alone, and two or more adults living together in a common dwelling who share basic finances. Thus, adults who live together but are unrelated and unmarried—such as housemates, roomers, a cohabiting couple, resident employees, or adult children or other relatives who might contribute to the housing expenses but otherwise maintain separate finances—count as separate economic households.

The KnowledgePanel® sample design began as an equal probability sample with several enhancements incorporated to improve efficiency. Since any alteration in the selection process is a deviation from a pure equal probability sample design, statistical weighting adjustments were made to the data to offset known selection deviations. These adjustments were incorporated in the sample's base weight.

There are also several sources of survey error that are an inherent part of any survey process, such as non-coverage and non-response due to panel recruitment methods and to inevitable panel attrition. These sources of sampling and non-sampling error were addressed using a panel demographic post-stratification weight.

Lastly, a set of study-specific post-stratification weights were constructed to adjust for the study's sample design and survey non-response. The 2010–11 MacroMonitor study-specific weights are based on household level demographic and geographic distributions for the non-institutionalized, civilian population ages 18+ from the Current Population Survey (CPS), March 2010 Supplement. Respondents were weighted to the derived benchmark distributions presented in Table 1.

Comparable distributions were calculated using all completed cases from the field data. Since study sample sizes are typically too small to accommodate a complete cross-tabulation of all the survey benchmark variables, an iterative proportional fitting is used for the post-stratification weighting adjustment. This procedure adjusts the sample data to the selected benchmark proportions. Through an iterative convergence process, the weighted sample data were optimally fitted to the marginal distributions.

After this post-stratification adjustment, the distribution of the weights were examined to identify and, if necessary, trim outliers at the extreme upper tail of the weight distribution. Extremely large weights, though they help the fit of the total sample to the Census marginals, are statistically very unreliable. And because the demographics of persons underrepresented (and overweighted) in the sample are typically the young, low income, and poorly educated, large weights also increase the relative importance of questionnaire responses of low validity. For these reasons, we capped the largest weights by winsorizing the distribution: We replaced the top 2.5% of weights by the mean value of the top 2.5% of weights. After winsorizing, the range of weights was 0.03 to 7.05. The post-stratified and trimmed weights were then scaled to the size of the population of economic households in the United States. The final weights ranged from 0.74 to 206.51 (ratio 279) and summed to 128,045(000) economic households.