The Impact of Typical Survey Weighting Adjustments on the Design Effect: A Case Study

Abstract

In survey sampling, the final sample weight assigned to each sampled unit reflects different steps of weighting adjustments such as frame integration, nonresponse and calibration. The analysis of the design effects for each of these adjustments casts light on their effects on the precision of survey estimates. In this paper, we limit our scope to the Canadian Community Health Survey (CCHS), briefly describe the weighting process of this survey and examine design effects at different steps of the weighting process to quantify how the overall variability in estimates can be attributed to the complex survey design and to each of the individual adjustments in the weighting process. As expected, the results suggest that the use of unequal person-selection probabilities and the nonresponse adjustment have the most negative impact on the design effect of the CCHS while calibration and winsorization decrease the design effect and improve the precision of the estimates.