Conditional Versus Unconditional Covariate Effects in Pharmacometric Models: Implications for Interpretation, Communication, and Reporting.

ABSTRACT: This work investigates how correlations between covariates influence the estimation of their effects in pharmacometric models. The focus is on quantifying the impact on conditional and unconditional covariate effect estimates and assessing the consequences for model interpretation, communication, and dosing recommendations. A theoretical framework was used to describe the mathematical relationship between conditional and unconditional coefficients. This was verified by simulations across a wide range of covariate correlation strengths and relative covariate effect sizes. The practical consequences of misinterpreting conditional effects were evaluated in the context of dose selection and a priori dose individualization. As predicted by theory, covariate correlation had a substantial effect

SUBMITTER: Jonsson EN 

PROVIDER: S-EPMC12849216 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature