Simultaneous confidence intervals based on the percentile bootstrap approach

Micha Mandel*, Rebecca A. Betensky

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

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

Bibliographical note

Funding Information:
This research was supported in part by NIH CA075971, the Harvard Center for Neurodegeneration and Repair (HCNR), and the Partners MS Center. We thank Howard Weiner for the permission to use the MS data.

Keywords

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

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