title: Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians.
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.
authors.affiliation: Medical Statistics Unit, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, U.K.
authors.forename: J
authors.initials: J
authors.lastname: Carpenter
authors.forename: J
authors.initials: J
authors.lastname: Bithell
mesh_terms: D000465:Algorithms; D001724:Birth Weight; D003198:Computer Simulation; D016001:Confidence Intervals; D004358:Drug Therapy / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007231:Infant, Newborn / Q000254:growth & development; D015470:Leukemia, Myeloid, Acute / Q000188:drug therapy; D008954:Models, Biological; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic; D012074:Remission Induction; D055502:Secondary Prevention