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Activity Number:
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469
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #308506 |
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Title:
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The Cost of Checking Proportional Hazards
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Author(s):
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Bryan Shepherd*+
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Companies:
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Vanderbilt University
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Address:
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1161 21st Avenue South, Nashville, TN, 37232,
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Keywords:
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survival analysis ; Cox regression ; bootstrap ; prediction ; model uncertainty ; AIDS
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Abstract:
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Confidence intervals (CI) and the reported predictive ability of statistical models may be misleading if one ignores uncertainty in the model selection procedure. When analyzing time-to-event data using Cox regression, one typically checks the proportional hazards (PH) assumption and subsequently alters the model to address any violations. Such an examination and correction constitutes a model selection procedure, and if not accounted for could result in misleading CI. With the bootstrap, I study the impact of checking the PH assumption using (1) data to predict AIDS-free survival among HIV-infected patients initiating antiretroviral therapy, and (2) simulated data. CI that adjust for the PH check tend to have similar or better coverage. The impact of checking the PH assumption is greatest when the p-value of the test for PH is close to the test's chosen Type I error probability.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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