plot.aalen | R Documentation |
This function plots the non-parametric cumulative estimates for the additive risk model or the test-processes for the hypothesis of time-varying effects with re-sampled processes under the null.
## S3 method for class 'aalen'
plot(
x,
pointwise.ci = 1,
hw.ci = 0,
sim.ci = 0,
robust.ci = 0,
col = NULL,
specific.comps = FALSE,
level = 0.05,
start.time = 0,
stop.time = 0,
add.to.plot = FALSE,
mains = TRUE,
xlab = "Time",
ylab = "Cumulative coefficients",
score = FALSE,
...
)
x |
the output from the "aalen" function. |
pointwise.ci |
if >1 pointwise confidence intervals are plotted with lty=pointwise.ci |
hw.ci |
if >1 Hall-Wellner confidence bands are plotted with lty=hw.ci. Only 0.95 % bands can be constructed. |
sim.ci |
if >1 simulation based confidence bands are plotted with lty=sim.ci. These confidence bands are robust to non-martingale behaviour. |
robust.ci |
robust standard errors are used to estimate standard error of estimate, otherwise martingale based standard errors are used. |
col |
specifice colors of different components of plot, in order: c(estimate,pointwise.ci,robust.ci,hw.ci,sim.ci) so for example, when we ask to get pointwise.ci, hw.ci and sim.ci we would say c(1,2,3,4) to use colors as specified. |
specific.comps |
all components of the model is plotted by default, but a list of components may be specified, for example first and third "c(1,3)". |
level |
gives the significance level. |
start.time |
start of observation period where estimates are plotted. |
stop.time |
end of period where estimates are plotted. Estimates thus plotted from [start.time, max.time]. |
add.to.plot |
to add to an already existing plot. |
mains |
add names of covariates as titles to plots. |
xlab |
label for x-axis. |
ylab |
label for y-axis. |
score |
to plot test processes for test of time-varying effects along with 50 random realization under the null-hypothesis. |
... |
unused arguments - for S3 compatibility |
Thomas Scheike
Martinussen and Scheike, Dynamic Regression models for Survival Data, Springer (2006).
# see help(aalen)
data(sTRACE)
out<-aalen(Surv(time,status==9)~chf+vf,sTRACE,max.time=7,n.sim=100)
par(mfrow=c(2,2))
plot(out,pointwise.ci=1,hw.ci=1,sim.ci=1,col=c(1,2,3,4))
par(mfrow=c(2,2))
plot(out,pointwise.ci=0,robust.ci=1,hw.ci=1,sim.ci=1,col=c(1,2,3,4))
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