Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package

Presenter: Samer Mouksassi, Certara
Sponsored by the Statistics and Pharmacometrics Special Interest Group for ASA and ISoP: sxpsig.github.io/
The current webinar describes why forest plots are needed for an effective communication of covariates effects, how they are constructed, and how they should be presented. Simulation- based methodologies, using mrgsolve, are presented and allow the user to evaluate the marginal impact of changing one covariate at a time or by considering the joint effects of correlated covariates are introduced along with graphical tools for an optimal assessment of the covariate effects. The R package coveffectsplot and an associated R Shiny application are provided to facilitate the design and construction of forest plots for the visualization of covariate effects. All codes and materials are available on a public github repository.