Validation of the smooth test of goodness-of-fit for proportional hazards in Cancer survival studies

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dc.contributor.authorOdhiambo, Collins
dc.contributor.authorOdhiambo, John
dc.contributor.authorOmolo, Bernard
dc.date.accessioned2021-05-11T09:47:55Z
dc.date.available2021-05-11T09:47:55Z
dc.date.issued2017
dc.descriptionPaper presented at the 4th Strathmore International Mathematics Conference (SIMC 2017), 19 - 23 June 2017, Strathmore University, Nairobi, Kenya.en_US
dc.description.abstractIn this study, we validate the smooth test of goodness-of-fit for the proportionality of the hazard function in the two-sample problem in cancer survival studies. The smooth test considered here is an extension of Neyman’s smooth test for proportional hazard functions. Simulations are conducted to compare the performance of the smooth test, the data-driven smooth test, the Kolmogorov-Smirnov proportional hazards test and the global test, in terms of power. Eight real cancer datasets from different settings are assessed for the proportional hazard assumption in the Cox proportional hazard models, for validation. The smooth test performed best and is independent of the number of covariates in the Cox proportional hazard models.en_US
dc.description.sponsorshipStrathmore University University of South Carolina-Upstateen_US
dc.identifier.urihttp://hdl.handle.net/11071/11810
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectCanceren_US
dc.subjectCox proportional hazards modelen_US
dc.subjectGlobal testen_US
dc.subjectNeyman’s smooth testen_US
dc.subjectTwo-sample problemen_US
dc.titleValidation of the smooth test of goodness-of-fit for proportional hazards in Cancer survival studiesen_US
dc.typeArticleen_US
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