PlotBayesSurv: Plot the posterior mean with credible band for the survival...

In BayesSurvival: Bayesian Survival Analysis for Right Censored Data

Description

This function takes the output from BayesSurv and uses ggplot2 to make plots of (1) the posterior mean of the survival function with credible band, or (2) the posterior mean of the cumulative hazard with credible band, or (3) the posterior mean of the cumulative hazard. Users can select some plotting options within this function. Further changes to the plot can be made by storing the plot and adding ggplot2 syntax (see the examples).

Usage

PlotBayesSurv(
  bayes.surv.object,
  object = c("survival", "cumhaz", "hazard"),
  band = TRUE,
  color = "darkblue",
  plot.title = "",
  xlab = "time",
  ylab = "",
  legend = TRUE,
  alpha.band = 0.4
)

Arguments

bayes.surv.object	The output from the function BayesSurv.
object	The object to be plotted, the user may select "survival" for the survival function, "cumhaz" for the cumulative hazard, or "hazard" for the hazard function. Default is the survival function.
band	Indicator whether a credible band should be plotted (only possible for the survival function and the cumulative hazard).
color	The color to be used for the posterior mean and the credible band (if applicable).
plot.title	A title for the plot.
xlab	A label for the horizontal axis.
ylab	a label for the vertical axis.
legend	If TRUE, a legend saying 'Credible band' will be included.
alpha.band	The transparency of the credible band.

Details

The posterior mean of the hazard and the posterior mean and credible band of the cumulative hazard are plotted exactly. The survival is plotted exactly at the points contained in the vector surv.eval.grid contained in the object created by BayesSurv. Between these points, the survival is linearly interpolated. To evaluate the survival exactly at more points (and to obtain a smoother plot), increase the parameter surv.factor within BayesSurv.

Value

gg	The plot, which may be edited further by adding ggplot2 syntax.

References

Castillo and Van der Pas (2020). Multiscale Bayesian survival analysis. <arXiv:2005.02889>.

See Also

BayesSurv to create the required object for this plotting function.

Examples

#Demonstration on a simulated data set
library(simsurv)
library(ggplot2)
hazard.true <- function(t,x, betas, ...){1.2*(5*(t+0.05)^3 - 10*(t+0.05)^2 + 5*(t+0.05) ) + 0.7}
sim.df <- data.frame(id = 1:1000)
df <- simsurv(x = sim.df, maxt = 1, hazard = hazard.true)

bs <- BayesSurv(df, "eventtime", "status")
PlotBayesSurv(bs, object = "survival")

cumhaz.plot <- PlotBayesSurv(bs, object = "cumhaz")
cumhaz.plot + labs(title = "Cumulative hazard")

BayesSurvival documentation built on March 13, 2021, 1:07 a.m.