ABSTRACT The inadequate control of sample sizes in surveys using stratified sampling and area estimation may occur when the overall sample size is small or auxiliary information is insufficiently used. Very small sample sizes are possible for some areas. The proposed allocation based on multi-objective optimization uses a small-area model and estimation method and semi-collected empirical data annually collected empirical data. The assessment of its performance at the area and at the population levels is based on design-based sample simulations. Five previously developed allocations serve as references. The model-based estimator is more accurate than the design-based Horvitz–Thompson estimator and the model-assisted regression estimator. Two trade-off issues are between accuracy and bias and between the area- and the population-level qualities of estimates. If the survey uses model-based estimation, the sampling design should incorporate the underlying model and the estimation method.

中文翻译：

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在样本分配中注册数据以进行小区域估计

摘要 当总体样本量较小或辅助信息使用不充分时，可能会出现使用分层抽样和面积估计的调查中样本量控制不充分的情况。某些地区的样本量可能非常小。基于多目标优化的建议分配使用小区域模型和估计方法和半收集经验数据每年收集的经验数据。其在该地区和人口层面的绩效评估基于基于设计的样本模拟。五个先前开发的分配可作为参考。基于模型的估计量比基于设计的 Horvitz-Thompson 估计量和模型辅助回归估计量更准确。两个权衡问题是准确性和偏差之间以及估计的区域和人口级别质量之间。如果调查使用基于模型的估计，抽样设计应结合基础模型和估计方法。