Nonparametric goodness-of-fit testing for parametric covariate models in pharmacometric analyses.

ABSTRACT: The characterization of covariate effects on model parameters is a crucial step during pharmacokinetic/pharmacodynamic analyses. Although covariate selection criteria have been studied extensively, the choice of the functional relationship between covariates and parameters, however, has received much less attention. Often, a simple particular class of covariate-to-parameter relationships (linear, exponential, etc.) is chosen ad hoc or based on domain knowledge, and a statistical evaluation is limited to the comparison of a small number of such classes. Goodness-of-fit testing against a nonparametric alternative provides a more rigorous approach to covariate model evaluation, but no such test has been proposed so far. In this manuscript, we derive and evaluate nonparametric goodness-of-fit

SUBMITTER: Hartung N 

PROVIDER: S-EPMC8213422 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature