plot.probtrans {mstate} | R Documentation |
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("stacked","filled","single","separate"),ord, cols,xlab="Time",ylab="Probability",ylim,lwd,lty,cex, legend,legend.pos,bty="o",...)
x |
Object of class 'probtrans', containing estimated transition probabilities |
from |
The starting state from which the probabilities are used to plot |
type |
One of "stacked" (default), "filled" ,
"single" or "separate" ; in case of "stacked" , the
transition probabilities are stacked and the distance between two
adjacent curves indicates the probability, this is also true for
"filled" , but the space between adjacent curves are filled,
in case of "single" , the probabilities are shown as different
curves in a single plot, in case of "separate" , separate plots
are shown for the estimated transition probabilities |
ord |
A vector of length equal to the number of states, specifying
the order of plotting in case type="stacked" or "filled" |
cols |
A vector specifying colors for the different transitions;
default is 1:K (K no of transitions), when type="single" , and
1 (black), when type="separate" |
xlab |
A title for the x-axis; default is "Time" |
ylab |
A title for the y-axis; default is
"Probability" |
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 par ; default is 1 |
lty |
The line type, see par ; default is 1 |
cex |
|
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 legend ;
default is "topleft" |
bty |
The box type of the legend, see legend |
... |
Further arguments to plot |
No return value
Hein Putter H.Putter@lumc.nl
# transition matrix for illness-death model tmat <- trans.illdeath() # data in wide format, for transition 1 this is dataset E1 of # Therneau & 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 & 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))