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Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians
Author(s) -
Carpenter James,
Bithell John
Publication year - 2000
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(20000515)19:9<1141::aid-sim479>3.0.co;2-f
Subject(s) - confidence interval , resampling , flow chart , computer science , statistics , confidence distribution , robust confidence intervals , strengths and weaknesses , chart , cdf based nonparametric confidence interval , data mining , mathematics , artificial intelligence , psychology , social psychology , engineering drawing , engineering
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. Copyright © 2000 John Wiley & Sons, Ltd.