On the impact of bootstrap in survey sampling and small-area estimation

被引：4

作者：

Lahiri, R ^{[1
]}

机构：

[1] Univ Maryland, Joint Program Survey Methodol, College Pk, MD 20855 USA

来源：

STATISTICAL SCIENCE | 2003年 / 18卷 / 02期

关键词：

imputation; resampling; small-area estimation; survey weights;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];

摘要：

Development of valid bootstrap procedures has been a challenging problem for survey samplers for the last two decades. This is due to the fact that in surveys we constantly face various complex issues such as complex correlation structure induced by the survey design, weighting, imputation, small-area estimation, among others. In this paper, we critically review various bootstrap methods developed to deal with these challenging issues. We discuss two applications where the bootstrap has been found to be effective.

引用

页码：199 / 210

页数：12

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