Using Auxiliary Information and Nonparametric Methods in Weighting Adjustments

摘要: Weighting adjustments are commonly used in survey estimation to compensate for unequal selection probabilities, nonresponse, noncoverage, and sampling fluctuations from known population values. Over time many weighting methods have been proposed, mainly the nonresponse framework. These generally make use of auxiliary variables reduce bias estimators improve their efficiency. Frequently, a substantial amount information is available choice way which they employed may be significant. Moreover, efficacy often seen as bias–variance trade-off. In this chapter, we analyze these aspects investigate properties mean adjusted by individual response probabilities estimated through nonparametric situations where multiple covariates both categorical continuous.