Abstract Details
Activity Number:
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88
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Type:
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Invited
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Date/Time:
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Sunday, August 3, 2014 : 8:30 PM to 10:30 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract #314102
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Title:
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Assessing the Fit of Parametric Cure Models
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Author(s):
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E. Paul Wileyto*+ and Yimei Li and Jinbo Chen and Daniel F. Heitjan
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Companies:
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University of Pennsylvania and Children's Hospital of Philadelphia and University of Pennsylvania Perelman School of Medicine and University of Pennsylvania
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Keywords:
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Accelerated failure time ;
Long-term survivors ;
Proportional hazards ;
Residual analysis
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Abstract:
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Survival data often contain an unknown fraction of subjects who are "cured" in the sense of not being at risk of failure. "Cure-mixture models" describe these data, which model both cure status and the hazard of failure among non-cured subjects with separate linear predictors. No diagnostic currently exists for evaluating the fit of such models; the popular Schoenfeld residual (Schoenfeld (1982) Biometrika 69, 239-241) is not applicable to data with cures. In this article, we develop a pseudo-residual, based on Schoenfeld's, to assess the fit of the survival regression in the non-cured fraction. Unlike Schoenfeld's approach, which tests the validity of the proportional hazards (PH) assumption, our method uses the full hazard and is thus also applicable to non-PH models. We derive the asymptotic distribution of the residuals and evaluate their performance by simulation in a range of parametric models. We demonstrate our approach using time to failure data from a smoking cessation drug trial.
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Authors who are presenting talks have a * after their name.
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