dpasurv (version 0.1.0)

ggplot.effect: Plot effects from dynamic path analysis along with bootstrap confidence bands

Description

plotting method for class "effect"

Usage

ggplot.effect(
  object,
  relative = FALSE,
  titles = NULL,
  x_label = "Time",
  y_label = NULL
)

Value

ggplot object

Arguments

object

object of class "effect", or list of objects of class "effect"

relative

should the effect be plotted on a relative survival scale (i.e. `y=exp(-effect)`)?. Defaults to FALSE.

titles

If NULL, function will automatically generate. Otherwise character vector of length equal to number of elements in object list

x_label

Label for x-axis. Defaults to "Time"

y_label

Label for y-axis. Default when object scale is "cumulative" will be "Cumulative Effect" (relative=FALSE) and "Relative survival" (relative=TRUE). If object scale is "identity" then the default y_label will be "Effect".

Examples

library(dpasurv)

data(simdata)

set.seed(1)

# Perform dynamic path analysis:
# We set boot.n=30 for the example to run fast, should be set large enough
# so that results don't change meaningfully for different seeds.
s <- dpa(Surv(start,stop,event)~M+x, list(M~x), id="subject", data=simdata, boot.n=30)

direct <- effect(x ~ outcome, s)
indirect <- effect(x ~ M ~ outcome, s)
total <- sum(direct, indirect)

ggplot.effect(direct)
ggplot.effect(list(direct, indirect, total))