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Abstract Details
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Activity Number:
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474
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #301099 |
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Title:
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An Alternative to ANCOVA When Standard Assumptions Are Untenable
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Author(s):
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J. Brooke Marshall*+ and Devan V. Mehrotra
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Companies:
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Merck Research Laboratories and Merck Research Laboratories
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Address:
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2 N Ridge Ave Apt 2F, Ambler, PA, 19002,
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Keywords:
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Analysis of Covariance ;
Discretization ;
Minimum Risk Weights ;
SP-EFFIC method ;
Stratification
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Abstract:
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In a simple analysis of covariance (ANCOVA) analysis for a randomized clinical trial, it is assumed that the response variable (Y) is linearly related to the baseline covariate (X), and that the variance of Y is constant across all levels of X. A violation of either assumption can result in a suboptimal analysis. We propose an alternate approach in which the continuous variable X is discretized to form three categorical strata, and a stratified analysis using "minimum risk" stratum weights (Mehrotra and Railkar, 2000) is then used for estimation and inference. The operating characteristics of our proposed approach will be contrasted with those of the usual ANCOVA and the SP-EFFIC method of Tsiatis et al. (Stat Med, 2007) using simulations. A vaccine clinical trial will be used for illustration.
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