Bootstrap hypothesis testing for some common statistical problems: A critical evaluation of size and power properties.

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dc.contributor.authorMartin, Michael
dc.date.accessioned2015-12-07T22:16:47Z
dc.date.issued2007
dc.date.updated2015-12-07T07:57:14Z
dc.description.abstractThe construction of bootstrap hypothesis tests can differ from that of bootstrap confidence intervals because of the need to generate the bootstrap distribution of test statistics under a specific null hypothesis. Similarly, bootstrap power calculations rely on resampling being carried out under specific alternatives. We describe and develop null and alternative resampling schemes for common scenarios, constructing bootstrap tests for the correlation coefficient, variance, and regression/ANOVA models. Bootstrap power calculations for these scenarios are described. In some cases, null-resampling bootstrap tests are equivalent to tests based on appropriately constructed bootstrap confidence intervals. In other cases, particularly those for which simple percentile-method bootstrap intervals are in routine use such as the correlation coefficient, null-resampling tests differ from interval-based tests. We critically assess the performance of bootstrap tests, examining size and power properties of the tests numerically using both real and simulated data. Where they differ from tests based on bootstrap confidence intervals, null-resampling tests have reasonable size properties, outperforming tests based on bootstrapping without regard to the null hypothesis. The bootstrap tests also have reasonable power properties.
dc.identifier.issn0167-9473
dc.identifier.urihttp://hdl.handle.net/1885/18190
dc.publisherElsevier
dc.sourceComputational Statistics and Data Analysis
dc.subjectKeywords: Computer simulation; Mathematical models; Probabilistic logics; Problem solving; Bootstrap confidence interval; Correlation coefficient; Null and alternative hypothesis; Resampling; Statistical methods Bootstrap confidence interval; Correlation coefficient; Null and alternative hypothesis; Power of test; Resampling; Size of test
dc.titleBootstrap hypothesis testing for some common statistical problems: A critical evaluation of size and power properties.
dc.typeJournal article
local.bibliographicCitation.issue12
local.bibliographicCitation.lastpage6342
local.bibliographicCitation.startpage6321
local.contributor.affiliationMartin, Michael, College of Business and Economics, ANU
local.contributor.authoremailu8517524@anu.edu.au
local.contributor.authoruidMartin, Michael, u8517524
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor010401 - Applied Statistics
local.identifier.absseo970101 - Expanding Knowledge in the Mathematical Sciences
local.identifier.ariespublicationu8517524xPUB3
local.identifier.citationvolume51
local.identifier.doi10.1016/j.csda.2007.01.020
local.identifier.scopusID2-s2.0-34547159345
local.identifier.uidSubmittedByu8517524
local.type.statusPublished Version

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