CASANOVA: permutation inference in factorial survival designs

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dc.contributor.authorDitzhaus, Marc
dc.contributor.authorGenuneit, Jon
dc.contributor.authorJanssen, Arnold
dc.contributor.authorPauly, Markus
dc.date.accessioned2023-04-17T13:37:31Z
dc.date.available2023-04-17T13:37:31Z
dc.date.issued2021-10-05
dc.description.abstractWe propose inference procedures for general factorial designs with time-to-event endpoints. Similar to additive Aalen models, null hypotheses are formulated in terms of cumulative hazards. Deviations are measured in terms of quadratic forms in Nelson–Aalen-type integrals. Different from existing approaches, this allows to work without restrictive model assumptions as proportional hazards. In particular, crossing survival or hazard curves can be detected without a significant loss of power. For a distribution-free application of the method, a permutation strategy is suggested. The resulting procedures' asymptotic validity is proven and small sample performances are analyzed in extensive simulations. The analysis of a data set on asthma illustrates the applicability.en
dc.identifier.urihttp://hdl.handle.net/2003/41339
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-23182
dc.language.isoende
dc.relation.ispartofseriesBiometrics;79(1)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectAdditive Aalen modelen
dc.subjectFactorial designsen
dc.subjectLocal alternativesen
dc.subjectOncologyen
dc.subjectRight censoringen
dc.subject.ddc310
dc.titleCASANOVA: permutation inference in factorial survival designsen
dc.typeTextde
dc.type.publicationtypearticlede
dcterms.accessRightsopen access
eldorado.secondarypublicationtruede
eldorado.secondarypublication.primarycitationDitzhaus, M., Genuneit, J., Janssen, A. & Pauly, M. (2023) CASANOVA: Permutation inference in factorial survival designs. Biometrics, 79, 203– 215. https://doi.org/10.1111/biom.13575de
eldorado.secondarypublication.primaryidentifierhttps://doi.org/10.1111/biom.13575de

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