Operational characteristics of full random effects modelling ('frem') compared to stepwise covariate modelling ('scm').

ABSTRACT: An adequate covariate selection is a key step in population pharmacokinetic modelling. In this study, the automated stepwise covariate modelling technique ('scm') was compared to full random effects modelling ('frem'). We evaluated the power to identify a 'true' covariate (covariate with highest correlation to the pharmacokinetic parameter), precision, and accuracy of the parameter-covariate estimates. Furthermore, the predictive performance of the final models was assessed. The scenarios varied in covariate effect sizes, number of individuals (n = 20-500) and covariate correlations (0-90% cov-corr). The PsN 'frem' routine provides a 90% confidence intervals around the covariate effects. This was used to evaluate its operational characteristics for a statistical backward elimination proced

SUBMITTER: Amann LF 

PROVIDER: S-EPMC10374720 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature