contsurvplot
Visualize the Effect of a Continuous Variable on a Time-to-Event Outcome
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.3 |
rolling linux/jammy R-4.5 | contsurvplot_0.2.3.tar.gz |
973.5 KiB |
0.2.3 |
rolling linux/noble R-4.5 | contsurvplot_0.2.3.tar.gz |
973.4 KiB |
0.2.3 |
rolling source/ R- | contsurvplot_0.2.3.tar.gz |
1.8 MiB |
0.2.3 |
latest linux/jammy R-4.5 | contsurvplot_0.2.3.tar.gz |
973.5 KiB |
0.2.3 |
latest linux/noble R-4.5 | contsurvplot_0.2.3.tar.gz |
973.4 KiB |
0.2.3 |
latest source/ R- | contsurvplot_0.2.3.tar.gz |
1.8 MiB |
0.2.3 |
2026-04-26 source/ R- | contsurvplot_0.2.3.tar.gz |
1.8 MiB |
0.2.3 |
2026-04-23 source/ R- | contsurvplot_0.2.3.tar.gz |
1.8 MiB |
0.2.3 |
2026-04-09 windows/windows R-4.5 | contsurvplot_0.2.3.zip |
975.2 KiB |
0.2.1 |
2025-04-20 source/ R- | contsurvplot_0.2.1.tar.gz |
1.8 MiB |