Prediction-Corrected Visual Predictive Checks for Diagnosing Nonlinear Mixed-Effects Models

@article{Bergstrand2011PredictionCorrectedVP,
  title={Prediction-Corrected Visual Predictive Checks for Diagnosing Nonlinear Mixed-Effects Models},
  author={Martin Bergstrand and Andrew C. Hooker and Johan E. Wallin and Mats O. Karlsson},
  journal={The AAPS Journal},
  year={2011},
  volume={13},
  pages={143-151}
}
Informative diagnostic tools are vital to the development of useful mixed-effects models. The Visual Predictive Check (VPC) is a popular tool for evaluating the performance of population PK and PKPD models. Ideally, a VPC will diagnose both the fixed and random effects in a mixed-effects model. In many cases, this can be done by comparing different percentiles of the observed data to percentiles of simulated data, generally grouped together within bins of an independent variable. However, the… CONTINUE READING
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