plot.cmp.rel  R Documentation 
Plot method for cmp.rel. Plots the cumulative probability of death due to disease and due to population reasons
## S3 method for class 'cmp.rel' plot( x, main = " ", curvlab, ylim = c(0, 1), xlim, wh = 2, xlab = "Time (days)", ylab = "Probability", lty = 1:length(x), xscale = 1, col = 1, lwd = par("lwd"), curves, conf.int, all.times = FALSE, ... )
x 
a list, with each component representing one curve in the plot,
output of the function 
main 
the main title for the plot. 
curvlab 
Curve labels for the plot. Default is 
ylim 
yaxis limits for plot. 
xlim 
xaxis limits for plot (default is 0 to the largest time in any of the curves). 
wh 
if a vector of length 2, then the upper right coordinates of the legend; otherwise the legend is placed in the upper right corner of the plot. 
xlab 
X axis label. 
ylab 
y axis label. 
lty 
vector of line types. Default 
xscale 
Scale of the X axis. Default is in days (1). 
col 
vector of colors. If 
lwd 
vector of line widths. If 
curves 
Vector if integers, specifies which curves should be plotted.
May take values 
conf.int 
Vector if integers, specifies which confidence intervals
should be plotted. May take values 
all.times 
By default, the disease specific mortality estimate is
plotted as a step function between event or censoring times. If set to

... 
additional arguments passed to the initial call of the plot function. 
By default, the graph is plotted as a step function for the cause specific mortality and as a piecewise linear function for the population mortality. It is evaluated at all event and censoring times even though it constantly changes also between these time points.
If the argument all.times
is set to TRUE
, the plot is
evaluated at all times that were used for numerical integration in the
cmp.rel
function (there, the default is set to daily intervals). If
only specific time points are to be added, this should be done via argument
add.times
in cmp.rel
.
No value is returned.
rs.surv
data(slopop) data(rdata) fit < cmp.rel(Surv(time,cens)~sex,rmap=list(age=age*365.241), ratetable=slopop,data=rdata,tau=3652.41) plot(fit,col=c(1,1,2,2),xscale=365.241,conf.int=c(1,3))
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