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Finite Population Sampling With Multivariate Auxiliary Information

Roger L. Wright
Journal of the American Statistical Association
Vol. 78, No. 384 (Dec., 1983), pp. 879-884
DOI: 10.2307/2288199
Stable URL: http://www.jstor.org/stable/2288199
Page Count: 6
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Finite Population Sampling With Multivariate Auxiliary Information
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Abstract

This article examines strategies that are approximately design-unbiased and nearly optimal, assuming a large-sample survey and a regression superpopulation model. A new class of predictors is proposed to link certain features of optimal design-unbiased and model-unbiased predictors. Generalized regression predictors are shown to pervade the subclass of asymptotically design-unbiased (ADU) predictors. Generalized regression predictors are combined with model-based stratification to construct highly efficient ADU strategies.

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