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Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians

Statistics in Medicine · 2000 · Vol. 19(9) · pp. 1141–1164

James R. Carpenter✉(University of London)John F. Bithell(University of Oxford)

Abstract

Since the early 1980s, a bewildering array of methods for constructing bootstrap confidence intervals have been proposed. In this article, we address the following questions. First, when should bootstrap confidence intervals be used. Secondly, which method should be chosen, and thirdly, how should it be implemented. In order to do this, we review the common algorithms for resampling and methods for constructing bootstrap confidence intervals, together with some less well known ones, highlighting their strengths and weaknesses. We then present a simulation study, a flow chart for choosing an appropriate method and a survival analysis example.

Statistical Methods in Clinical Trials Statistical Methods and Bayesian Inference Statistical Methods and InferenceConfidence intervalResamplingFlow chartComputer scienceStatisticsConfidence distributionRobust confidence intervalsStrengths and weaknessesChartCDF-based nonparametric confidence interval

MeSH terms

AlgorithmsBirth WeightComputer SimulationDrug TherapyHumansInfantInfant, NewbornModels, BiologicalRemission InductionLeukemia, Myeloid, AcuteConfidence IntervalsProportional Hazards ModelsRandomized Controlled Trials as TopicSecondary Prevention

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