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Activity Number: 3
Type: Invited
Date/Time: Sunday, July 29, 2012 : 2:00 PM to 3:50 PM
Sponsor: Biopharmaceutical Section
Abstract - #303494
Title: The Role of Direct Likelihood, Inverse Probability Weighting, and Multiple Imputation for the Analysis of Incomplete Trial Data
Author(s): Geert Molenberghs*+
Companies: I-BioStat/Universiteit Hasselt/Katholieke Universiteit Leuven
Address: Agoralaan 1, Diepenbeek, International, 3590, Belgium
Keywords: incomplete data ; sensitiviity analysis ; direct likelihood ; inverse probability weighting ; multiple imputatoin

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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