Use of Estimating Functions for Estimation from Complex Surveys

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Abstract
We describe a method for point and interval estimation of population parameters from complex surveys using estimating functions. The theory was originally developed for infinite populations and has recently been applied to finite populations. With estimating functions, a unifying framework can be given for point and interval estimation of both finite and infinite population parameters. We discuss test inversion methods to derive confidence intervals for one-dimensional parameters and propose a method for eliminating nuisance parameters in the multidimensional setting. We show that special cases of our proposal result in conditional and orthogonal methods proposed in the literature. We describe a simulation study using real data to compare the coverage probabilities of confidence intervals obtained under various approaches.

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