Paradata for Nonresponse Error Investigation

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 differen...

Macro and Micro Paradata for Survey Assessment

At present we typically assess quality by relying heavily on summary process measures or macro paradata that is a by-product of sample selection and survey administration (e.g., item and unit nonresponse rates, response variances, sampling and coverage errors). These measures are an outgrowth of the randomization-based approach to survey sampling that triumphed in government agencies around the...

Nonresponse prediction in an establishment survey using combination of statistical learning methods

Nonrespose is a source of error in the survey results and national statistical organizations are always looking for ways to control and reduce it. Predicting nonrespons sampling units in the survey before conducting the survey is one of the solutions that can help a lot in reducing and treating the survey nonresponse. Recent advances in technology and the facilitation of complex calculations...

Indicators For Monitoring And Improving Representativeness Of Response

The increasing efforts and costs required to achieve survey response have led to a stronger focus on survey data collection monitoring by means of paradata and to the rise of adaptive and responsive survey designs. Indicators that support data collection monitoring, targeting and prioritizing in such designs are not yet available. Subgroup response rates come closest but do not account for subg...

Collecting Paradata for Measurement Error Evaluations