Paradata for Nonresponse Adjustment

Survey researchers and practitioners use nonresponse adjustment weights to mitigate the effects of survey nonresponse on sample estimates. One challenge in creating these weights is finding useful auxiliary data that predict both the probability of participating in the survey and the survey variables of interest. This article reviews the use of paradata for nonresponse adjustment. Five different types of paradata are considered: neighborhood observations, observations of the sampled housing unit, observations of persons in the sampled housing unit, call records, and observations about the interviewer-householder interaction. Empirical evidence about the predictive value of these paradata for predicting both participation and survey variables is examined. Challenges of using these paradata are also identified, along with outstanding issues and opportunities related to the use of paradata for nonresponse adjustment.