Assessing and comparing the accuracy of various bootstrap methods

Yaqian Zhu, John Kolassa

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


We evaluate the performance of various bootstrap methods for constructing confidence intervals for mean and median of several common distributions. Using Monte Carlo simulation, we assessed performance by looking at coverage percentages and average confidence interval lengths. Poor performance is characterized by coverage deviating from 0.95 and large confidence interval lengths. Undercoverage is of greater concern than overcoverage. We also assess the performance of bootstrap methods in estimating the parameters of the Cox Proportional Hazard model and Accelerated Failure Time model.

Original languageEnglish (US)
Pages (from-to)2436-2453
Number of pages18
JournalCommunications in Statistics: Simulation and Computation
Issue number8
StatePublished - Sep 14 2018

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation


  • Accelerated failure time model
  • Bootstrap
  • Cox regression model


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