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Abstract Details
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Activity Number:
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3
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Type:
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Invited
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Date/Time:
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Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #303494 |
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Title:
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The Role of Direct Likelihood, Inverse Probability Weighting, and Multiple Imputation for the Analysis of Incomplete Trial Data
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Author(s):
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Geert Molenberghs*+
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Companies:
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I-BioStat/Universiteit Hasselt/Katholieke Universiteit Leuven
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Address:
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Agoralaan 1, Diepenbeek, International, 3590, Belgium
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Keywords:
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incomplete data ;
sensitiviity analysis ;
direct likelihood ;
inverse probability weighting ;
multiple imputatoin
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Abstract:
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Direct likelihood, inverse probability weighting, doubly robust methods, and multiple imputation are becoming ever more prevalent for the analysis of incomplete clinical trial data, especially with longitudinally measured outcomes. While they are often perceived as competitive with one another, we argue that they can fit together nicely and actually complement each other in an encompassing analysis, including sensitivity analysis, of such clinical trial data. Arguably, the document put forward by Little et al. (2010) makes important contributions towards such unifying efforts.
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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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