Confidence intervals for survival quantiles in the Cox regression model |
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Authors: | Tze Leung Lai Zheng Su |
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Institution: | (1) Department of Statistics, Stanford University, Stanford, CA 94305, USA;(2) Department of Applied Mathematics and Statistics, SUNY Stony Brook, Stony Brook, NY 11733, USA |
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Abstract: | Median survival times and their associated confidence intervals are often used to summarize the survival outcome of a group
of patients in clinical trials with failure-time endpoints. Although there is an extensive literature on this topic for the
case in which the patients come from a homogeneous population, few papers have dealt with the case in which covariates are
present as in the proportional hazards model. In this paper we propose a new approach to this problem and demonstrate its
advantages over existing methods, not only for the proportional hazards model but also for the widely studied cases where
covariates are absent and where there is no censoring. As an illustration, we apply it to the Stanford Heart Transplant data.
Asymptotic theory and simulation studies show that the proposed method indeed yields confidence intervals and bands with accurate
coverage errors. |
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Keywords: | Bootstrap Median survival Proportional hazards model Test-based confidence intervals and bands |
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