Simultaneous confidence intervals based on the percentile bootstrap approach

Micha Mandel, Rebecca Betensky

Research output: Contribution to journalArticle

Abstract

This note concerns the construction of bootstrap simultaneous confidence intervals (SCI) for m parameters. Given B bootstrap samples, we suggest an algorithm with complexity of O (mB log (B)). We apply our algorithm to construct a confidence region for time dependent probabilities of progression in multiple sclerosis and for coefficients in a logistic regression analysis. Alternative normal based simultaneous confidence intervals are presented and compared to the bootstrap intervals.

Original languageEnglish (US)
Pages (from-to)2158-2165
Number of pages8
JournalComputational Statistics and Data Analysis
Volume52
Issue number4
DOIs
StatePublished - Jan 10 2008

Fingerprint

Simultaneous Confidence Intervals
Percentile
Bootstrap
Multiple Sclerosis
Bootstrap Confidence Intervals
Confidence Region
Logistic Regression
Progression
Regression Analysis
Regression analysis
Logistics
Interval
Alternatives
Coefficient
Confidence interval

Keywords

  • Bonferroni
  • Confidence region
  • Discrete survival curve
  • Multiple sclerosis
  • Normal bound

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Statistics, Probability and Uncertainty
  • Electrical and Electronic Engineering
  • Computational Mathematics
  • Numerical Analysis
  • Statistics and Probability

Cite this

Simultaneous confidence intervals based on the percentile bootstrap approach. / Mandel, Micha; Betensky, Rebecca.

In: Computational Statistics and Data Analysis, Vol. 52, No. 4, 10.01.2008, p. 2158-2165.

Research output: Contribution to journalArticle

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