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dc.contributor.authorLiu, Shifang
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2011-09-27 11:09:28.449en
dc.date.accessioned2011-09-27T16:03:21Z
dc.date.available2011-09-27T16:03:21Z
dc.date.issued2011-09-27
dc.identifier.urihttp://hdl.handle.net/1974/6758
dc.descriptionThesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2011-09-27 11:09:28.449en
dc.description.abstractTreatment–covariate interaction is often used in clinical trials to assess the homogeneity of treatment effects over these subgroups defined by a baseline covariate, which is frequently conducted after primary analysis including all patients is completed. When the endpoint is the time to an event, as in the cancer clinical trials, the Cox proportional hazard model with an interaction term has been used exclusively to test the significance of treatment-covariate interaction in oncology literature. But the proportional hazards assumption may not be satisfied by the data from clinical trials. Although there are several procedures proposed in statistical literature to assess the interaction based on a nonparametric measure of interaction or nonparametric models, some of these procedures do not take into the account of the nature of the data well, while some are very complicated which may have limited their applications in practice. In this thesis, a non-parametric procedure based on the smoothed estimate of Patel–Hoel measure is first derived to test the interaction between the treatment and a binary covariate with censored data. The theoretical distribution of the test statistic of the proposed procedure is derived. The proposed procedure is also evaluated through Monte-Carlo simulations and applications to data from a cancer clinical trial. Jackknifed versions of two test statistics based on nonparametric models are then derived by simplifying these test statistics and applying the jackknife method to estimate their variances. These jackknifed tests are also compared with the smoothed test and other related tests.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectJackknife estimateen_US
dc.subjectMonte-Carlo simulationen_US
dc.subjectnonparametric measure of interactionen_US
dc.subjectKernel smoothen_US
dc.titleStatistical Methods for Testing Treatment-Covariate Interactions in Cancer Clinical Trialsen_US
dc.typeThesisen_US
dc.description.degreePh.Den
dc.contributor.supervisorTu, Dongshengen
dc.contributor.departmentMathematics and Statisticsen


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