plot.kmciLR: Plot and lines methods for 'kmci', 'kmciLR', 'kmciLRtidy',...

In bpcp: Beta Product Confidence Procedure for Right Censored Data

Plot and lines methods for kmci, kmciLR, kmciLRtidy, and kmciLRgroup objects.

Description

Plots survival curves and/or confidence intervals. kmciLR objects from the bpcp function will plot using base R plot. If a kmciLRtidy object is created using bpcpfit (plotstyle = "ggplot"), the plot will display using ggplot. If a kmciLRgroup object is created using bpcpfit (plotstyle = "standard"), the plot will display using base R.

Usage

## S3 method for class 'kmci'
plot(x, ...)

## S3 method for class 'kmciLR'
plot(x, XLAB = "time", YLAB = "Survival", YLIM = c(0, 1), 
    ciLTY = 2, ciCOL = gray(0.8), mark.time = NULL, 
    linetype = "both", ...)

## S3 method for class 'kmciLR'
lines(x, lty = c(2, 1), col = c(gray(0.8), gray(0)), 
    linetype = "both", mark.time = NULL, ...)

## S3 method for class 'kmci'
lines(x, ...)

## S3 method for class 'kmciLRtidy'
plot(x, ...)
                          
## S3 method for class 'kmciLRgroup'
plot(x,XLAB="Time",YLAB="Survival",
 YLIM=c(0,1),ciLTY=2,ciCOL=gray(.8), linetype="both", ...)

Arguments

x	kmci, kmciLR, kmciLRtidy, or kmciLRgroup object (created by functions described in kmtestALL)
XLAB	label for x axis
YLAB	label for y axis
YLIM	limits for y axis
ciLTY	lty (line type) for confidence intervals
ciCOL	col (color) for confidence intervals
col	vector of colors, first element used for ci second for survival curve
lty	vector of line types, first element used for ci second for survival curve
mark.time	put hash marks for censored objects (default puts marks of stype="km" but not if stype="mue")
linetype	character, which lines to draw: either 'both', 'surv' or 'ci'
...	Extra parameters to be passed. Any argument in plot.kmciLR can be passed from plot.kmci, similarly for line. Other parameters are usually graphical parameters passed to plot and segment calls within function.

Examples

data(leuk)
## kmciTG creates kmci object
fitTG<-kmciTG(leuk$time,leuk$status)
plot(fitTG)
## bpcp creates kmciLR object 
fitBP<-bpcp(leuk$time,leuk$status)
lines(fitBP,lwd=3,lty=1,col=gray(.5),linetype="ci")
legend(0,.2,legend=c("Kaplan-Meier","Thomas-Grunkemeier 95 pct C
I","Beta Product 95 pct CI"),
    lwd=c(1,1,3),lty=c(1,2,1),col=c(gray(0),gray(.8),gray(.5)))
data(leuk2)
## bpcpfit creates kmciLR object which is plotted with ggplot
fitBPsurv <- bpcpfit(Surv(time, status)~treatment, data=leuk2)
plot(fitBPsurv)
## this works even if no treatment variable is specified
plot(bpcpfit(Surv(time, status)~1, data=leuk2))

## if plotstyle "standard" is specified, a base R plot is produced
a <- bpcpfit(leuk2$time, leuk2$status, leuk2$treatment, plotstyle = "standard")
plot(a)

#can also create a tidy object to customize ggplot further
tidy <- tidykmciLR(fitBPsurv)
ggplot(tidy, aes(x = time, y = surv, ymin = lower, ymax = upper, col = group)) + 
  geom_line(show.legend=FALSE) + geom_ribbon(alpha = .2, aes(fill=group)) + 
  xlab("Time") + ylab("Survival") + 
  ggtitle("K-M curves with bpcp CIs") 

bpcp documentation built on March 18, 2022, 6:25 p.m.