Statistical Science

On the Impact of Bootstrap in Survey Sampling and Small-Area Estimation

P. Lahiri

Full-text: Open access

Abstract

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.

Article information

Source
Statist. Sci., Volume 18, Issue 2 (2003), 199-210.

Dates
First available in Project Euclid: 19 September 2003

Permanent link to this document
https://projecteuclid.org/euclid.ss/1063994975

Digital Object Identifier
doi:10.1214/ss/1063994975

Mathematical Reviews number (MathSciNet)
MR2019788

Zentralblatt MATH identifier
1331.62076

Keywords
Imputation resampling small-area estimation survey weights

Citation

Lahiri, P. On the Impact of Bootstrap in Survey Sampling and Small-Area Estimation. Statist. Sci. 18 (2003), no. 2, 199--210. doi:10.1214/ss/1063994975. https://projecteuclid.org/euclid.ss/1063994975


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