A novel method based on unbiased correlations tests for covariate selection in nonlinear mixed effects models: The COSSAC approach.

ABSTRACT: Building a covariate model is a crucial task in population pharmacokinetics and pharmacodynamics in order to understand the determinants of the interindividual variability. Identifying a good covariate model usually requires many runs. Several procedures have been proposed in the past to automatize this task. The most commonly used is Stepwise Covariate Modeling (SCM). Here, we present a novel stepwise method based on statistical tests between individual parameters sampled from their conditional distribution and the covariates. This strategy, called the COnditional Sampling use for Stepwise Approach based on Correlation tests (COSSAC), makes use of the information contained in the current model to choose which parameter-covariate relationship to try next. This strategy greatly reduces the

SUBMITTER: Ayral G 

PROVIDER: S-EPMC8099437 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature