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Model averaging inconcentration–QT analyses
Authors:Bernard Sébastien  David Hoffman  Clémence Rigaux  Franck Pellissier  Jérôme Msihid
Institution:1. Department of Biostatistics and Programming, SANOFI R&D, Chilly‐Mazarin, France;2. Biometrics, Abbvie, North Chicago, IL, USA;3. Department of Biostatistics and Programming, SANOFI R&D, Montpellier, France
Abstract:This article describes how a frequentist model averaging approach can be used for concentration–QT analyses in the context of thorough QTc studies. Based on simulations, we have concluded that starting from three candidate model families (linear, exponential, and Emax) the model averaging approach leads to treatment effect estimates that are quite robust with respect to the control of the type I error in nearly all simulated scenarios; in particular, with the model averaging approach, the type I error appears less sensitive to model misspecification than the widely used linear model. We noticed also few differences in terms of performance between the model averaging approach and the more classical model selection approach, but we believe that, despite both can be recommended in practice, the model averaging approach can be more appealing because of some deficiencies of model selection approach pointed out in the literature. We think that a model averaging or model selection approach should be systematically considered for conducting concentration–QT analyses. Copyright © 2016 John Wiley & Sons, Ltd.
Keywords:model averaging  model selection  concentration–  QT analysis  thorough QTc study
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