Improving traditional nonresponse bias adjustments Combining statistical properties with social theory

Declining response rates have led to increasing reliance on nonresponse adjustment as a way to reduce the risk of nonresponse bias. Unfortunately, the auxiliary variables used in most surveys frequently do not satisfy the sine qua non for effective adjustment: significant associations with both nonresponse and the survey variables. We describe an approach to selecting weight variables that identifies candidates, such as voting and volunteering, not usually considered. In an analysis of the 2012 General Social Survey (GSS), we show that voting eligibility, voter turnout, and candidate choice meet the statistical conditions for nonresponse bias reduction, as does volunteering. Voting and volunteering are strongly associated with participation in the GSS and also associated with a wide array of variables measured in the GSS. Adjustments using either voting benchmarks or volunteering benchmarks result in significant changes to GSS estimates compared to traditional adjustments. As this approach shows promise, we identify several lines of research needed to inform its implementation.

Peytchev, A., Presser, S., & Zhang, M. (2018). Improving traditional nonresponse bias adjustments: Combining statistical properties with social theory. Journal of Survey Statistics and Methodology. DOI: 10.1093/jssam/smx035