survminer 0.2.3
New features
- New function
surv_summary()
for creating data frame containing a nice summary of a survival curve (#64). - It's possible now to facet the output of
ggsurvplot()
by one or more factors (#64):
# Fit complexe survival curves
require("survival")
fit3 <- survfit( Surv(time, status) ~ sex + rx + adhere,
data = colon )
# Visualize by faceting
# Plots are survival curves by sex faceted by rx and adhere factors.
require("survminer")
ggsurv$plot +theme_bw() + facet_grid(rx ~ adhere)
- Now,
ggsurvplot()
can be used to plot cox model (#67). - New 'myeloma' data sets added.
- New functions added for determining and visualizing the optimal cutpoint of continuous variables for survival analyses:
surv_cutpoint()
: Determine the optimal cutpoint for each variable using 'maxstat'. Methods defined for surv_cutpoint object are summary(), print() and plot().surv_categorize()
: Divide each variable values based on the cutpoint returned bysurv_cutpoint()
(#41).
- New argument 'ncensor.plot' added to
ggsurvplot()
. A logical value. If TRUE, the number of censored subjects at time t is plotted. Default is FALSE (#18).
Minor changes
- New argument 'conf.int.style' added in
ggsurvplot()
for changing the style of confidence interval bands. - Now,
ggsurvplot()
plots a stepped confidence interval when conf.int = TRUE (#65). ggsurvplot()
updated for compatibility with the future version of ggplot2 (v2.2.0) (#68)- ylab is now automatically adapted according to the value of the argument
fun
. For example, if fun = "event", then ylab will be "Cumulative event". - In
ggsurvplot()
, linetypes can now be adjusted by variables used to fit survival curves (#46) - In
ggsurvplot()
, the argument risk.table can be either a logical value (TRUE|FALSE) or a string ("absolute", "percentage"). If risk.table = "absolute",ggsurvplot()
displays the absolute number of subjects at risk. If risk.table = "percentage", the percentage at risk is displayed. Use "abs_pct" to show both the absolute number and the percentage of subjects at risk. (#70). - New argument surv.median.line in
ggsurvplot()
: character vector for drawing a horizontal/vertical line at median (50%) survival. Allowed values include one of c("none", "hv", "h", "v"). v: vertical, h:horizontal (#61). - Now, default theme of ggcoxdiagnostics() is ggplot2::theme_bw().
Bug fixes
ggcoxdiagnostics()
can now handle a multivariate Cox model (#62)ggcoxfunctional()
now displays graphs of continuous variable against martingale residuals of null cox proportional hazards model (#63).- When subset is specified in the survfit() model, it's now considered in
ggsurvplot()
to report the right p-value on the subset of the data and not on the whole data sets (@jseoane, #71). ggcoxzph()
can now produce plots only for specified subset of varibles (@MarcinKosinski, #75)