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Statistical power of goodness-of-fit tests based on the empirical distribution function for type-I right-censored data

dc.contributor.authorBispo, Regina
dc.contributor.authorMarques, Tiago A.
dc.contributor.authorPestana, Dinis
dc.date.accessioned2012-11-07T21:05:45Z
dc.date.available2012-11-07T21:05:45Z
dc.date.issued2012
dc.description.abstractIn this study, the power of common goodness-of-fit (GoF) statistics based on the empirical distribution function (EDF) was simulated for single type-I right-censored data. The statistical power of the Kolmogorov–Smirnov, Cramér–von Mises and Anderson–Darling statistics was investigated by varying the null and the alternative distributions, the sample size, the degree of censoring and the significance level. The exponential,Weibull, log-logistic and log-normal lifetime distributions were considered as they are among the most frequently distributions used when modelling censored data. We conclude by giving some general recommendations for testing the distributional assumption of parametric survival models in homogeneous populations when using EDF-based GoF statistics.por
dc.identifier.citationJournal of Satistical Computation and Simulation, 82 (2), 173-181por
dc.identifier.issn0094-9655
dc.identifier.urihttp://hdl.handle.net/10400.12/1809
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherTaylor & Francispor
dc.subjectCensored datapor
dc.subjectGoodness-of-fitpor
dc.subjectLifetime distributionspor
dc.subjectPowerpor
dc.subjectType-I censoringpor
dc.titleStatistical power of goodness-of-fit tests based on the empirical distribution function for type-I right-censored datapor
dc.typejournal article
dspace.entity.typePublication
oaire.citation.conferencePlaceOxfordpor
oaire.citation.endPage181por
oaire.citation.startPage173por
oaire.citation.titleJournal of Satistical Computation and Simulationpor
oaire.citation.volume82por
rcaap.rightsrestrictedAccesspor
rcaap.typearticlepor

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