Bootstrap Variance Estimation for Rejective Sampling

Wayne A. Fuller, Jason C. Legg, Yang Li

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Replication procedures have proven useful for variance estimation for large scale complex surveys. As an extension of bootstrap procedures to rejective samples, we define a bootstrap sample that is a rejective, unequal probability, replacement sample selected from the original sample. A modification of the bootstrap with improved performance is suggested for stratified samples with small stratum sizes. Simulations for Poisson and stratified rejective samples support the use of replicates in estimating the variance of the regression estimator for rejective samples.

Original languageEnglish (US)
Pages (from-to)1562-1570
Number of pages9
JournalJournal of the American Statistical Association
Volume112
Issue number520
DOIs
StatePublished - Oct 2 2017

Bibliographical note

Publisher Copyright:
© 2017 American Statistical Association.

Keywords

  • Balanced sampling
  • Controlled sampling
  • Poisson sampling
  • Replication variance

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