Fellow in the Survey Research Division at RTI International  

Survey data producers increasingly provide estimates of nonresponse bias in several variables when they release or analyze data. Researchers understand that sample estimates of population values should be reported with appropriate measures of uncertainty, such as standard errors or confidence intervals. However, few studies acknowledge that nonresponse bias estimates are also subject to sampling variability. Using simulations, we study the sampling variability of nonresponse bias estimates and how that variability is affected by features such as clustering and response rates. We then evaluate three methods to estimate the sampling variance for nonresponse bias estimates and provide guidance to researchers.