Journal
CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY
Volume 11, Issue 10, Pages 1283-1293Publisher
WILEY
DOI: 10.1002/psp4.12829
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This tutorial explains the importance of forest plots in communicating covariate effects effectively, the construction methods, and presentation techniques. It also introduces simulation-based methodologies and graphical tools for evaluating covariate effects, along with providing an R package and application for designing and constructing forest plots.
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.
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