Use of a linearization approximation facilitating stochastic model building.

ABSTRACT: The objective of this work was to facilitate the development of nonlinear mixed effects models by establishing a diagnostic method for evaluation of stochastic model components. The random effects investigated were between subject, between occasion and residual variability. The method was based on a first-order conditional estimates linear approximation and evaluated on three real datasets with previously developed population pharmacokinetic models. The results were assessed based on the agreement in difference in objective function value between a basic model and extended models for the standard nonlinear and linearized approach respectively. The linearization was found to accurately identify significant extensions of the model's stochastic components with notably decreased runtimes as co

SUBMITTER: Svensson EM 

PROVIDER: S-EPMC3969514 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature