Post-Strata Based on Sample Quantiles
提出用辅助变量的样本分布函数定义后分层边界，避免空层问题，大样本效率与基于总体的方法相同，模拟显示新方法效率略高且置信区间覆盖更准。
Abstract The standard method of creating post-strata is to define the boundaries of the strata on the basis of population characteristics of auxiliary variables. Estimation treats the post-strata as strata for standard stratified-sample estimation. Samples often contain empty post-strata requiring adjustment to the estimation procedure. To avoid empty post-strata, we propose using the sample distribution function of an auxiliary variable to define the post-strata. We show that the large-sample efficiency of the sample-based post-stratification procedure is the same as that of the equivalently defined population-based procedure. In the simulation, the sample-based procedure was slightly more efficient than the classical procedure. The Monte Carlo coverage of a nominal 95% interval was approximately 95% for the sample-based procedure and approximately 94% for the classical procedure.