plotRate {reReg} | R Documentation |
Plotting the Baseline Cumulative Rate Function for the Recurrent Event Process
Description
Plot the baseline cumulative rate function for an reReg
object.
Usage
plotRate(
x,
newdata = NULL,
frailty = NULL,
showName = FALSE,
type = c("unrestricted", "bounded", "scaled"),
smooth = FALSE,
control = list(),
...
)
Arguments
x |
an object of class |
newdata |
an optional data frame contains variables to include in the calculation of the cumulative rate function. If omitted, the baseline rate function will be plotted. |
frailty |
an optional vector to specify the shared frailty for |
showName |
an optional logical value indicating whether to label the curves
when |
type |
a character string specifying the type of rate function to be plotted. Options are "unrestricted", "scaled", "bounded". See Details. |
smooth |
an optional logical value indicating whether to add a smooth curve
obtained from a monotone increasing P-splines implemented in package |
control |
a list of control parameters. |
... |
graphical parameters to be passed to methods.
These include |
Details
The plotRate()
plots the estimated baseline cumulative rate function
depending on the identifiability assumption.
When type = "unrestricted"
(default), the baseline cumulative rate function
is plotted under the assumption E(Z) = 1
.
When type = "scaled"
, the baseline cumulative rate function is plotted
under the assumption \Lambda(\min(Y^\ast, \tau)) = 1
.
When type = "bounded"
, the baseline cumulative rate function is plotted
under the assumption \Lambda(\tau) = 1
.
See ?reReg
for the specification of the notations and underlying models.
The argument control
consists of options with argument defaults
to a list with the following values:
- xlab
customizable x-label, default value is "Time".
- ylab
customizable y-label, default value is empty.
- main
customizable title, default value is "Baseline cumulative rate function".
These arguments can also be specified outside of the control
list.
Value
A ggplot
object.
See Also
Examples
data(simDat)
fm <- Recur(t.start %to% t.stop, id, event, status) ~ x1 + x2
fit <- reReg(fm, data = simDat, model = "cox|cox", B = 0)
## Plot both the baseline cumulative rate and hazard function
plot(fit)
## Plot baseline cumulative rate function
plotRate(fit)
plotRate(fit, smooth = TRUE)