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Are Response Rates to Web-Only Surveys Spatially Clustered? Implications for Understanding Geographic Bias and Coverage in General Population Web Surveys
Lee Fiorio
NORC at the University of Chicago
Michael Stern
NORC at the University of Chicago
Ned English
NORC at the University of Chicago
To date, there is little empirical information about the role space and place has in estimating forms of error associated with Web-only surveys. One way to pursue this issue of place is to use Geographic Information Systems (GIS) to spatially-model survey response rates. This will allow us to understand the impact of location on error in Web surveys. In this paper, we attempt to examine this gap in the literature by assessing the spatial clustering of response rates to a Web-only survey. The data come from a random, Address- Based Sampling Approach using the Delivery Sequence File (Valassis version) where respondents received a postal letter with a URL. We calculate response rates at several geographic scales, including county, state, and region, to determine the extent to which response rates are spatially clustered. While controlling for ACS demographics, internet availability, and postal characteristics, we then build a spatial lag model to measure spatial dependence of response rates observed. Preliminary findings show clusters of low response rates in the South that cannot be accounted for by other variables in the model.