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To address current limitations with model diagnostic graphics and efficiency of the workflow for this software, we developed an R package, Phxnlme, to facilitate its workflow and provide improved graphical diagnostics.
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Goodness-of-fit (GOF) plots are the primary diagnostic graphics used to evaluate model adequacy.
The stability of the model and accuracy of the parameters were assessed by a bootstrap method implemented in Wings for Nonmem [ 18] and diagnostic graphics and distribution statistics were obtained using R for Nonmem [ 18] via the R program [ 19].
The AMGET package was therefore developed to offer a broad selection of highly informative diagnostic graphics, featuring dependent variable vs. time plots, goodness-of-fit plots, post hoc fits, posterior mean estimates distribution of model parameters and VPC plots.
Diagnostic graphics and other statistics were derived using the R software program [ 16].
The primary objective of AMGET was to improve end-user productivity by readily generating diagnostic graphics.
Diagnostic graphics were used for evaluation of the goodness-of-fit.
An extensive literature search failed to reveal any pre- or post-processing package for the creation of diagnostic graphics based upon the use of ADAPT 5 outputs.
Graphics can play an important and unique role in PopPK model diagnostics.
Our team developed a graphic pipeline to generate a collection of plots and statistics for PopPK model diagnostics.
Model diagnostics.
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