The current tutorial 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 allowing 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.
© 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.