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<dc:description>AcknowledgementsThe authors would like to thank professor Ludwig Fahrmeir from the Institut fürStatistik at the Ludwig Maximilians University in Munich (Germany) for checking thismanuscript and his wise comments. Part of this work was completed at the Institut fürStatistik and we are most grateful for their hospitality.</dc:description>
<dc:description>The aim of this study is to define a new statistic, PVL, based on the relativedistance between the likelihood associated with the simulation replications and thelikelihood of the conceptual model. Our results coming from several simulationexperiments of a clinical trial show that the PVL statistic range can be a good measureof stability to establish when a computational model verifies the underlying conceptualmodel. PVL improves also the analysis of simulation replications because only onestatistic is associated with all the simulation replications. As well it presents severalverification scenarios, obtained by altering the simulation model, that show theusefulness of PVL. Further simulation experiments suggest that a 0 to 20 % range maydefine adequate limits for the verification problem, if considered from the viewpoint ofan equivalence test.</dc:description>
<dc:description>This research was supported by a scholarship from the Department of Statisticsat the University of Barcelona, grant no.: ACES-UB 2006.</dc:description>
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<dc:subject>Assaigs clínics</dc:subject>
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<mods:abstract>AcknowledgementsThe authors would like to thank professor Ludwig Fahrmeir from the Institut fürStatistik at the Ludwig Maximilians University in Munich (Germany) for checking thismanuscript and his wise comments. Part of this work was completed at the Institut fürStatistik and we are most grateful for their hospitality.</mods:abstract>
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