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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=contsurvplot to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4