Bootstrapping generalized linear models

Lawrence H. Moulton, Scott L. Zeger

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Several methods for bootstrapping generalized linear regression models are introduced. One-step techniques, both conditional and unconditional on the covariates, are examined with respect to robustness and coverage properties.

Original languageEnglish (US)
Pages (from-to)53-63
Number of pages11
JournalComputational Statistics and Data Analysis
Issue number1
StatePublished - Jan 1991


  • Bootstrap
  • Generalized linear models
  • Logistic regression
  • Overdispersion
  • Robustness

ASJC Scopus subject areas

  • Statistics and Probability
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics


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