Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package
Abstract 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 o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-10-01
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| Series: | CPT: Pharmacometrics & Systems Pharmacology |
| Online Access: | https://doi.org/10.1002/psp4.12829 |
| _version_ | 1798029799751417856 |
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| author | Jean‐Francois Marier Nathan Teuscher Mohamad‐Samer Mouksassi |
| author_facet | Jean‐Francois Marier Nathan Teuscher Mohamad‐Samer Mouksassi |
| author_sort | Jean‐Francois Marier |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-04-11T19:30:10Z |
| format | Article |
| id | doaj.art-c83b89f55cf64660b1be3521588802b9 |
| institution | Directory Open Access Journal |
| issn | 2163-8306 |
| language | English |
| last_indexed | 2024-04-11T19:30:10Z |
| publishDate | 2022-10-01 |
| publisher | Wiley |
| record_format | Article |
| series | CPT: Pharmacometrics & Systems Pharmacology |
| spelling | doaj.art-c83b89f55cf64660b1be3521588802b92022-12-22T04:07:01ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062022-10-0111101283129310.1002/psp4.12829Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R packageJean‐Francois Marier0Nathan Teuscher1Mohamad‐Samer Mouksassi2Certara Strategic Consulting Princeton New Jersey USACertara Strategic Consulting Princeton New Jersey USACertara Strategic Consulting Princeton New Jersey USAAbstract 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.https://doi.org/10.1002/psp4.12829 |
| spellingShingle | Jean‐Francois Marier Nathan Teuscher Mohamad‐Samer Mouksassi Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package CPT: Pharmacometrics & Systems Pharmacology |
| title | Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package |
| title_full | Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package |
| title_fullStr | Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package |
| title_full_unstemmed | Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package |
| title_short | Evaluation of covariate effects using forest plots and introduction to the coveffectsplot R package |
| title_sort | evaluation of covariate effects using forest plots and introduction to the coveffectsplot r package |
| url | https://doi.org/10.1002/psp4.12829 |
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