Speaker: Rebecca Andridge, PhD, Associate Professor, Biostatistics, The Ohio State University College of Public Health

When “representative” surveys fail: Can a nonignorable missingness mechanism explain bias in estimates of COVID-19 vaccine uptake?

Recently, attention was drawn to the “failure” of two very large internet-based probability surveys (Delphi-Facebook, Census Household Pulse) to correctly estimate COVID-19 vaccine uptake in the U.S. in early 2021. These surveys overestimated vaccine uptake substantially (14 and 17 points in May 2021) compared to retroactively available CDC benchmark data. Though very large, these surveys had very low response rates, thus non-ignorable nonresponse could have substantially impacted estimates. Specifically, it is plausible that “anti-vaccine” individuals were less likely to complete a survey about COVID-19; we might also hypothesize that “anti-vaccine” individuals could be suspicious of the government and thus less likely to respond to an official government-sponsored survey. In this talk we use proxy pattern-mixture models (PPMMs) to retrospectively estimate the proportion of adults who received at least one vaccine dose, using data from these two surveys, under a non-ignorable nonresponse assumption. We compare these estimates to the true benchmark uptake numbers, enabling assessment of whether non-ignorable nonresponse is a plausible explanation for the biased estimates. We also use the PPMM to estimate vaccine hesitancy, a measure without a benchmark truth, and compare to the direct survey estimates.

Rebecca Andridge is an Associate Professor of Biostatistics at The Ohio State University College of Public Health. She conducts methodologic work in imputation methods for missing data, primarily in large-scale probability samples, and measures of selection bias for nonprobability samples. In particular, she works on methods for imputing data when missingness is driven by the missing values themselves (missing not at random). She teaches introductory graduate and undergraduate biostatistics and won the College's Outstanding Teaching Award in 2011 and is a Fellow of the American Statistical Association.