Empirical Likelihood Confidence Intervals for Complex Sampling Designs
复杂抽样设计下的经验似然置信区间
Summary We define an empirical likelihood approach which gives consistent design-based confidence intervals which can be calculated without the need of variance estimates, designeffects, resampling, joint inclusion probabilities and linearization, even when the point estimator is not linear. It can be used to construct confidence intervals for a large class of sampling designs and estimators which are solutions of estimating equations. It can be used for means, regressions…