Abstract Details
Activity Number:
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395
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Type:
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Contributed
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Date/Time:
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Tuesday, August 5, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract #312408
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View Presentation
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Title:
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Covariance Estimation of Favorable Proportion for Missing Dichotomous Data in a Multi-Visit Randomized Clinical Trial
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Author(s):
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Siying Li*+ and Gary Koch
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Companies:
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University of North Carolina at Chapel Hill and University of North Carolina at Chapel Hill
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Keywords:
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clinical trial ;
sensitivity analysis ;
missing data ;
longitudinal data ;
covariance estimation
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Abstract:
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This paper presents a closed form method for sensitivity analysis of a randomized multi-visit multi-center clinical trial that possibly has missing not at random (MNAR) dichotomous data. Counts of missing data are redistributed to the favorable outcomes probabilistically to adjust for possibly informative missing; adjusted proportion estimates as well as their closed form covariance estimates are provided. Treatment comparisons over time are addressed with adjustment for a stratification factor and/or baseline covariates. The parameter estimates are computed via weighted least square asymptotic regression through randomization based methods. Application of such sensitivity analyses are illustrated with an example.
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Authors who are presenting talks have a * after their name.
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