Automatic data binning for improved visual diagnosis of pharmacometric modelsReport as inadecuate




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* Corresponding author 1 POPIX - Modélisation en pharmacologie de population Inria Saclay - Ile de France

Abstract : Visual Predictive Checks VPC are graphical tools to help decide whether a given model could have plausibly generated a given set of real data. Typically, time-course data is binned into time intervals, then statistics are calculated on the real data and data simulated from the model, and represented graphically for each interval. Poor selection of bins can easily lead to incorrect model diagnosis. We propose an automatic binning strategy that improves reliability of model diagnosis using VPC. It is implemented in version 4 of the Monolix software.





Author: Marc Lavielle - Kevin Bleakley -

Source: https://hal.archives-ouvertes.fr/



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