The generalised bootstrap for clustered data

Zhen Pang, A. H. Welsh

Research output: Journal article publicationJournal articleAcademic researchpeer-review

3 Citations (Scopus)

Abstract

We extend the generalised bootstrap of Chatterjee and Bose (2005) to bootstrap clustered data. We show by simulations and theoretical arguments that the variance of the random weights used in the generalised bootstrap is critical in determining the performance of the bootstrap when we use the distribution of the bootstrap estimate to approximate the sampling distribution of the parameter. In particular, we show that for consistency, the weights should be chosen to have variance one.
Original languageEnglish
Pages (from-to)407-415
Number of pages9
JournalInternational Journal of Data Analysis Techniques and Strategies
Volume6
Issue number4
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Bootstrap
  • Clustered data
  • Generalised bootstrap
  • Quasi-likelihood estimation
  • Unbalanced data
  • Variance components

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management
  • Applied Mathematics

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