Boosting Probability-Based Web Survey Response Rates via Non-Response Follow-up By Angela Fontes, Kean Chew, and Paul Lavrakas Web surveys using probability sampleshave the advantage of known probabilities of selection for each sample unit and typically produce more representative samples than non-probability sample sources; however, such surveys typically have low AAPOR responses rates for a variety of reasons. This paper describes a case study for boosting the response rate for web surveys sourced from probability samples. The response-rate boosting methodology involves a few components: conducting the initial web survey with a probability sample; drawing a random sample of the non -responders (excluding ineligible sample units) for nonresponse follow-up; and conducting the non-response follow- up study using professional field staff recruiting the sample to participate in the web survey. In addition to describing the methodology, the paper will present perspective on the appropriate calculation of a weighted response rate and standard errors from the combined sample (sourced from the initial survey and the non-response follow-up study). The paper will provide statistical evidence on impact on the sample representativeness and statistical findings as a result of including the interviews obtained from the non-response follow-up study.