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Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: The npde add-on package for R.

Abstract : Pharmacokinetic/pharmacodynamic data are often analysed using nonlinear mixed-effect models, and model evaluation should be an important part of the analysis. Recently, normalised prediction distribution errors (npde) have been proposed as a model evaluation tool. In this paper, we describe an add-on package for the open source statistical package R, designed to compute npde. npde take into account the full predictive distribution of each individual observation and handle multiple observations within subjects. Under the null hypothesis that the model under scrutiny describes the validation dataset, npde should follow the standard normal distribution. Simulations need to be performed before hand, using for example the software used for model estimation. We illustrate the use of the package with two simulated datasets, one under the true model and one with different parameter values, to show how npde can be used to evaluate models. Model estimation and data simulation were performed using NONMEM version 5.1.
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https://www.hal.inserm.fr/inserm-00274332
Contributor : Emmanuelle Comets <>
Submitted on : Friday, April 18, 2008 - 11:19:38 AM
Last modification on : Wednesday, August 19, 2020 - 11:16:43 AM
Long-term archiving on: : Thursday, May 20, 2010 - 8:58:18 PM

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Emmanuelle Comets, Karl Brendel, France Mentré. Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: The npde add-on package for R.. Computer Methods and Programs in Biomedicine, Elsevier, 2008, 90 (2), pp.154-66. ⟨10.1016/j.cmpb.2007.12.002⟩. ⟨inserm-00274332⟩

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