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Article: A k-sample test with interval censored data

TitleA k-sample test with interval censored data
Authors
KeywordsGoodness Of Fit
Interval Censoring
Iterative Convex Minorant Algorithm
Leveraged Bootstrap
Nonparametric Maximum Likelihood
Issue Date2006
PublisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/
Citation
Biometrika, 2006, v. 93 n. 2, p. 315-328 How to Cite?
AbstractThe problem of testing for the equality of k distribution functions under Case 2 interval censoring is studied and a supremum-type test statistic is proposed based on the differences between the nonparametric maximum likelihood estimator and the so-called leveraged bootstrap estimator of the k underlying distributions. The proposed test is distributionfree and consistent against all alternatives. As the main results hold for a wide range of resampling sizes, a data-driven method is suggested for determining the size of each leveraged bootstrap sample. Another advantage of the test is that it can detect different distributions with equal means or heavy crossover. Simulation studies indicate that the test performs quite well with a moderate sample size. Finally, a slightly modified version of the test is applied to breast cosmesis data. © 2006 Biometrika Trust.
Persistent Identifierhttp://hdl.handle.net/10722/172423
ISSN
2015 Impact Factor: 1.13
2015 SCImago Journal Rankings: 2.801
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYuen, KCen_US
dc.contributor.authorShi, Jen_US
dc.contributor.authorZhu, Len_US
dc.date.accessioned2012-10-30T06:22:26Z-
dc.date.available2012-10-30T06:22:26Z-
dc.date.issued2006en_US
dc.identifier.citationBiometrika, 2006, v. 93 n. 2, p. 315-328en_US
dc.identifier.issn0006-3444en_US
dc.identifier.urihttp://hdl.handle.net/10722/172423-
dc.description.abstractThe problem of testing for the equality of k distribution functions under Case 2 interval censoring is studied and a supremum-type test statistic is proposed based on the differences between the nonparametric maximum likelihood estimator and the so-called leveraged bootstrap estimator of the k underlying distributions. The proposed test is distributionfree and consistent against all alternatives. As the main results hold for a wide range of resampling sizes, a data-driven method is suggested for determining the size of each leveraged bootstrap sample. Another advantage of the test is that it can detect different distributions with equal means or heavy crossover. Simulation studies indicate that the test performs quite well with a moderate sample size. Finally, a slightly modified version of the test is applied to breast cosmesis data. © 2006 Biometrika Trust.en_US
dc.languageengen_US
dc.publisherOxford University Press. The Journal's web site is located at http://biomet.oxfordjournals.org/en_US
dc.relation.ispartofBiometrikaen_US
dc.subjectGoodness Of Fiten_US
dc.subjectInterval Censoringen_US
dc.subjectIterative Convex Minorant Algorithmen_US
dc.subjectLeveraged Bootstrapen_US
dc.subjectNonparametric Maximum Likelihooden_US
dc.titleA k-sample test with interval censored dataen_US
dc.typeArticleen_US
dc.identifier.emailYuen, KC: kcyuen@hku.hken_US
dc.identifier.authorityYuen, KC=rp00836en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1093/biomet/93.2.315en_US
dc.identifier.scopuseid_2-s2.0-33745611103en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33745611103&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume93en_US
dc.identifier.issue2en_US
dc.identifier.spage315en_US
dc.identifier.epage328en_US
dc.identifier.eissn1464-3510-
dc.identifier.isiWOS:000238760600007-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridYuen, KC=7202333703en_US
dc.identifier.scopusauthoridShi, J=7404495329en_US
dc.identifier.scopusauthoridZhu, L=7404201068en_US
dc.identifier.citeulike722963-

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