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Activity Number:
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250
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Type:
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Contributed
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Date/Time:
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Tuesday, August 8, 2006 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #307057 |
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Title:
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Sensitivity of the Kaplan-Meier Estimate to Nonignorable Censoring
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Author(s):
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Tao Liu*+ and Daniel F. Heitjan
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Companies:
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University of Pennsylvania School of Medicine and University of Pennsylvania
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Address:
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Department of Biostatistics and Epidemiology, Philadelphia, PA, 19104,
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Keywords:
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coarse-data model ; ignorability ; informative censoring ; ISNI ; Kaplan-Meier curve ; sensitivity analysis
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Abstract:
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Untestable assumptions about association between survival and censoring times can affect the validity of estimates of the survival distribution, including the Kaplan-Meier (KM) nonparametric MLE. This article explores the sensitivity of KM to nonignorable censoring by extending the index of local sensitivity to nonignorability (ISNI) (Troxel, Ma, Heitjan 2004, Zhang 2004) to the case of a nonparametric survival model. The method involves first specifying a coarse-data selection model to describe the association between the failure and censoring processes, then evaluating the slope of the nonparametric survival MLE with respect to a nonignorability parameter in the neighborhood of the ignorable model. We show in a simulation that ISNI analysis captures local sensitivity to nonignorability well. We apply the method to the Stanford Heart Transplant Data.
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