Plot method for a probtrans object
Plot method for an object of class 'probtrans'. It plots the transition
probabilities as estimated by probtrans.
## S3 method for class 'probtrans'
plot(
x,
from = 1,
type = c("filled", "single", "separate", "stacked"),
ord,
cols,
xlab = "Time",
ylab = "Probability",
xlim,
ylim,
lwd,
lty,
cex,
legend,
legend.pos = "right",
bty = "n",
xaxs = "i",
yaxs = "i",
use.ggplot = FALSE,
conf.int = 0.95,
conf.type = c("log", "plain", "none"),
label,
...
)x |
Object of class 'probtrans', containing estimated transition probabilities |
from |
The starting state from which the probabilities are used to plot |
type |
One of |
ord |
A vector of length equal to the number of states, specifying the
order of plotting in case type= |
cols |
A vector specifying colors for the different transitions;
default is a palette from green to red, when type= |
xlab |
A title for the x-axis; default is |
ylab |
A title for the y-axis; default is |
xlim |
The x limits of the plot(s), default is range of time |
ylim |
The y limits of the plot(s); if ylim is specified for type="separate", then all plots use the same ylim for y limits |
lwd |
The line width, see |
lty |
The line type, see |
cex |
Character size, used in text; only used when
type= |
legend |
Character vector of length equal to the number of transitions, to be used in a legend; if missing, numbers will be used; this and the legend arguments following are ignored when type="separate" |
legend.pos |
The position of the legend, see |
bty |
The box type of the legend, see |
xaxs |
See |
yaxs |
See |
use.ggplot |
Default FALSE, set TRUE for ggplot version of plot |
conf.int |
Confidence level (%) from 0-1 for probabilities, default is 0.95 (95% CI). Setting to 0 removes the CIs. |
conf.type |
Type of confidence interval - either "log" or "plain" . See function details for details. |
label |
Only relevant for type = "filled" or "stacked", set to "annotate" to have state labels on plot, or leave unspecified. |
... |
Further arguments to plot |
Regarding confidence intervals: let p denote a predicted probability, σ its estimated standard error, and z_{α/2} denote the critical value of the standard normal distribution at confidence level 1 - α.
The confidence interval of type "plain" is then
p \pm z_{α/2} * σ
The confidence interval of type "log", based on the Delta method, is then
\exp(\log(p) \pm z_{α/2} * σ / p)
No return value
Hein Putter H.Putter@lumc.nl
Edouard F. Bonneville e.f.bonneville@lumc.nl
# transition matrix for illness-death model
tmat <- trans.illdeath()
# data in wide format, for transition 1 this is dataset E1 of
# Therneau and Grambsch (2000)
tg <- data.frame(illt=c(1,1,6,6,8,9),ills=c(1,0,1,1,0,1),
dt=c(5,1,9,7,8,12),ds=c(1,1,1,1,1,1),
x1=c(1,1,1,0,0,0),x2=c(6:1))
# data in long format using msprep
tglong <- msprep(time=c(NA,"illt","dt"),status=c(NA,"ills","ds"),
data=tg,keep=c("x1","x2"),trans=tmat)
# events
events(tglong)
table(tglong$status,tglong$to,tglong$from)
# expanded covariates
tglong <- expand.covs(tglong,c("x1","x2"))
# Cox model with different covariate
cx <- coxph(Surv(Tstart,Tstop,status)~x1.1+x2.2+strata(trans),
data=tglong,method="breslow")
summary(cx)
# new data, to check whether results are the same for transition 1 as
# those in appendix E.1 of Therneau and Grambsch (2000)
newdata <- data.frame(trans=1:3,x1.1=c(0,0,0),x2.2=c(0,1,0),strata=1:3)
msf <- msfit(cx,newdata,trans=tmat)
# probtrans
pt <- probtrans(msf,predt=0)
# default plot
plot(pt,ord=c(2,3,1),lwd=2,cex=0.75)
# filled plot
plot(pt,type="filled",ord=c(2,3,1),lwd=2,cex=0.75)
# single plot
plot(pt,type="single",lwd=2,col=rep(1,3),lty=1:3,legend.pos=c(8,1))
# separate plots
par(mfrow=c(2,2))
plot(pt,type="sep",lwd=2)
par(mfrow=c(1,1))
# ggplot version - see vignette for details
library(ggplot2)
plot(pt, ord=c(2,3,1), use.ggplot = TRUE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.