contsurvplot: Visualize the Effect of a Continuous Variable on a Time-to-Event Outcome (original) (raw)
Graphically display the (causal) effect of a continuous variable on a time-to-event outcome using multiple different types of plots based on g-computation. Those functions include, among others, survival area plots, survival contour plots, survival quantile plots and 3D surface plots. Due to the use of g-computation, all plot allow confounder-adjustment naturally. For details, see Robin Denz, Nina Timmesfeld (2023) <doi:10.1097/EDE.0000000000001630>.
| Version: | 0.2.1 |
|---|---|
| Imports: | ggplot2 (≥ 3.4.0), dplyr, rlang, riskRegression, foreach |
| Suggests: | survival, pammtools, gganimate, transformr, plotly, reshape2, doParallel, knitr, rmarkdown, testthat (≥ 3.0.0), vdiffr (≥ 1.0.0), covr |
| Published: | 2023-08-15 |
| DOI: | 10.32614/CRAN.package.contsurvplot |
| Author: | Robin Denz [aut, cre] |
| Maintainer: | Robin Denz <robin.denz at rub.de> |
| Contact: | robin.denz@rub.de |
| BugReports: | https://github.com/RobinDenz1/contsurvplot/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/RobinDenz1/contsurvplot,https://robindenz1.github.io/contsurvplot/ |
| NeedsCompilation: | no |
| Citation: | contsurvplot citation info |
| Materials: | README NEWS |
| CRAN checks: | contsurvplot results |
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