Predicting unit variate values in a finite population Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/mk61rk609

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  • The problem of predicting variate values for all individual units in a finite population based on a sample of some of the units is Investigated. Two prediction problems are considered: the one-stage prediction problem where the unit variate values are directly observable for each sample unit, and the two-stage prediction problem where the sample units are subsampled in order to estimate the variate values for these units. A superpopulation model-based approach is suggested to both of these problems. In both cases, a model framework is developed, predictors given for the unit variate values, and the error variances of these predictors are derived. An important aspect in the sample design of these prediction problems is the allocation of the sample. An algorithm Is developed for selecting specific units to be sampled. This selection procedure is used for the one-stage problem to derive a method for determining the number of units to sample to achieve a prespecified precision on the predictors. For the two-stage problem, a method is developed for selecting both the number of units and subunits to achieve a fixed sample size while minimizing the error variances of the predictors. An example is given that illustrates some of the theoretical results. Finally, the applicability of this approach is discussed and areas for further investigation are indicated.
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