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dc.creatorWu, Tingxuan 1987-
dc.date.accessioned2018-12-21T14:41:00Z
dc.date.available2018-12-21T14:41:00Z
dc.date.created2018-12
dc.date.issued2018-12-21
dc.date.submittedDecember 2018
dc.identifier.urihttp://hdl.handle.net/10388/11696
dc.description.abstractTraditional residuals for diagnosing accelerated failure time models in survival analysis, such as Cox-Snell, martingale and deviance residuals, have been widely used. However, ex- amining those residuals are often only made visually, which can be subjective. Therefore, lack of objective measure of examining model adequacy has been a long-standing issue that needs to be addressed for survival analysis. In this thesis, a new type of residual is proposed called Normal-transformed Randomized Survival Probability (NRSP) residual. A compre- hensive review of the traditional residuals including Cox Snell and deviance residuals is firstly presented highlighting their disadvantages for examining model adequacy. We then introduce NRSP residual. Simulation studies were conducted to compare the performance of NRSP residuals with the traditional residuals. Our simulation studies demonstrated that NRSP residuals are approximately normally distributed when the fitted model is correctly speci- fied, and has great statistical power in detecting model inadequacies. We also apply NRSP residuals to a real dataset to check the goodness-of-fit of three plausible models.
dc.format.mimetypeapplication/pdf
dc.subjectRSP
dc.subjectUCS
dc.subjectMCS
dc.subjectNCS
dc.titleRandomized Survival Probability Residual for Assessing Parametric Survival Models
dc.typeThesis
dc.date.updated2018-12-21T14:41:01Z
thesis.degree.departmentSchool of Public Health
thesis.degree.disciplineBiostatistics
thesis.degree.grantorUniversity of Saskatchewan
thesis.degree.levelMasters
thesis.degree.nameMaster of Science (M.Sc.)
dc.type.materialtext
dc.contributor.committeeMemberLi, Longhai
dc.contributor.committeeMemberFeng, Cindy
dc.contributor.committeeMemberKhan, Shahedul
dc.contributor.committeeMemberPahwa, Punam
dc.contributor.committeeMemberShao, Enchuan


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