An Analysis of Survival Data when Hazards are not Proportional: Application to a Cancer Treatment Study

dc.contributor.advisorYiannoutsos, Constantin
dc.contributor.authorWhite, John Benjamin
dc.contributor.otherBakoyannis, Giorgos
dc.contributor.otherFadel, William
dc.date.accessioned2022-01-03T17:05:46Z
dc.date.available2022-01-03T17:05:46Z
dc.date.issued2021-12
dc.degree.date2021en_US
dc.degree.disciplineBiostatisticsen
dc.degree.grantorIndiana Universityen_US
dc.degree.levelM.S.en_US
dc.descriptionIndiana University-Purdue University Indianapolis (IUPUI)en_US
dc.description.abstractThe crossing of Kaplan-Meier survival curves presents a challenge when conducting survival analysis studies, making it unclear whether any of the study groups involved present any significant difference in survival. An approach involving the determination of maximum vertical distance between the curves is considered here as a method to assess whether a survival advantage exists between different groups of patients. The method is illustrated on a dataset containing survival times of patients treated with two cancer treatment regimes, one involving treatment by chemotherapy alone, and the other by treatment with both chemotherapy and radiotherapy.en_US
dc.identifier.urihttps://hdl.handle.net/1805/27245
dc.identifier.urihttp://dx.doi.org/10.7912/C2/86
dc.language.isoen_USen_US
dc.subjectkaplan-meieren_US
dc.subjectcrossing survival curvesen_US
dc.subjectnonproportional hazardsen_US
dc.subjectsurvival analysisen_US
dc.titleAn Analysis of Survival Data when Hazards are not Proportional: Application to a Cancer Treatment Studyen_US
dc.typeThesisen
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