Abstract
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 in the nonresponse framework. These methods generally make use of auxiliary variables to reduce the bias of the estimators and improve their efficiency. Frequently, a substantial amount of auxiliary information is available and the choice of the auxiliary variables and the way in which they are employed may be significant. Moreover, the efficacy of weighting adjustments is often seen as a bias–variance trade-off. In this chapter, we analyze these aspects of the nonresponse weighting adjustments and investigate the properties of mean estimators adjusted by individual response probabilities estimated through nonparametric methods in situations where multiple covariates are both categorical and continuous.
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Rocco, E. (2013). Using Auxiliary Information and Nonparametric Methods in Weighting Adjustments. In: Torelli, N., Pesarin, F., Bar-Hen, A. (eds) Advances in Theoretical and Applied Statistics. Studies in Theoretical and Applied Statistics(). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35588-2_27
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DOI: https://doi.org/10.1007/978-3-642-35588-2_27
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