Abstract Details
Activity Number:
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194
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Type:
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Contributed
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Date/Time:
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Monday, August 10, 2015 : 10:30 AM to 12:20 PM
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Sponsor:
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ENAR
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Abstract #317137
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Title:
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Multiple Imputation of Missing Covariates for the Cure Model
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Author(s):
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Lauren Beesley* and Jeremy Taylor
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Companies:
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University of Michigan and University of Michigan
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Keywords:
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multiple imputation ;
missing data ;
cure models
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Abstract:
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Recently, various authors have proposed methods for imputing missing covariates for failure time data. However, covariate imputation methods are less developed for failure time data when a fraction of the population is considered cured and will never develop the event of interest. We propose several methods for imputing covariates via fully conditional specification that utilize the cure structure. A simulation study demonstrates that, under proportional hazards assumptions, our methods can produce efficiency gains in estimating cure model parameters compared to complete case analysis and imputation methods for survival outcomes without a cured fraction. We show that some gains can also been seen when proportional hazards assumptions have been violated. We apply our multiple imputation techniques to a study of previously untreated patients with Head and Neck Squamous cell carcinoma (HNSCC).
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Authors who are presenting talks have a * after their name.
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