Use of Estimating Functions for Estimation from Complex Surveys
本文描述了一种利用估计函数对复杂调查数据进行总体参数点估计和区间估计的方法，并讨论了消除多余参数的方法，通过模拟研究比较了不同方法的置信区间覆盖概率。
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.