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Plot estimated cumulative incidence functions (CIFs)

Source: R/plot_inc.R
plot_inc.Rd

This function plots the estimated potential cumulative incidence function, along with pointwise confidence intervals.

Usage

plot_inc(
  fit,
  decrease = FALSE,
  conf.int = 0.95,
  xlab = "Time",
  xlim = NULL,
  ylim = c(0, 1),
  plot.configs = list(ylab = NULL, main = NULL, lty = 1, lwd = 2, ci.lty = 5, ci.lwd =
    1.5, legend = c("Treated", "Control"), col = c("brown", "darkcyan"), legend.cex =
    0.9, show.p.value = TRUE),
  ...
)

Arguments

fit

A fitted object returned by the function tteICE, surv.tteICE, or scr.tteICE.

decrease

A logical variable indicating the type of curve to display. If decrease = FALSE (default), cumulative incidence functions (CIFs) are plotted. If decrease = TRUE, survival functions are plotted instead.

conf.int

Confidence level for the pointwise confidence intervals If conf.int = NULL, no confidence intervals are provided.

xlab

Label for the x-axis.

xlim

A numeric vector of length 2 specifying the limits of the x-axis. If xlim = NULL (default), the limits are determined automatically from the data.

ylim

A numeric vector of length 2 specifying the limits of the y-axis. Defaults to ylim = c(0, 1).

plot.configs

A named list of additional plot configurations. Common entries include:

  • ylab: character, label for the y-axis (default: ylab=NULL, use the default label).

  • main: character, title for the plot (default: main=NULL, use the default label).

  • lty: line type for the curve (default: lty=1).

  • lwd: line width for the curve (default: lwd=2).

  • ci.lty: line type for confidence interval curves (default: ci.lty=5, ci.lwd=1.5).

  • ci.lwd: line width for confidence interval curves (default: ci.lwd=1.5).

  • legend: legend for the two group (default: legend=c('Treated','Control')).

  • col: color of the curve for the two group (default: col=c('brown','darkcyan')).

  • legend.cex: font size for the legend (default: legend.cex=0.9).

  • show.p.value: whether to show the p-value between two groups (default: show.p.value=TRUE, show the p-value)

...

Additional graphical arguments passed to function plot.default or function curve

Value

Plot the cumulative incidence function results from a tteICE object

See also

plot.default, points, curve, plot.tteICE

Examples

## load data
data(bmt)
bmt = transform(bmt, d4=d2+d3)
A = as.numeric(bmt$group>1)
bmt$A = A

## simple model fitting and plotting
library(survival)
fit = tteICE(Surv(t2,d4,type = "mstate")~A, data=bmt)
plot_inc(fit)


## model fitting using competing risk data
fit1 = surv.tteICE(A, bmt$t2, bmt$d4, 'treatment')

## plot asymptotic confidence intervals based on explicit formulas
plot_inc(fit1, ylim=c(0,1),
         plot.configs=list(legend=c('AML','ALL'), show.p.value=FALSE) )


## plot bootstrap confidence intervals
fit2 = surv.tteICE(A, bmt$t2, bmt$d4, 'treatment', nboot=50)
plot_inc(fit2, ylim=c(0,1),
         plot.configs=list(legend=c('AML','ALL')))


## model fitting using semicompeting risk data
fit3 = scr.tteICE(A, bmt$t1, bmt$d1, bmt$t2, bmt$d2, "composite")

## plot asymptotic confidence intervals based on explicit formulas
plot_inc(fit3, ylim=c(0,1), plot.configs=list(add.null.line=FALSE))


## plot bootstrap confidence intervals
fit4 = scr.tteICE(A, bmt$t1, bmt$d1, bmt$t2, bmt$d2,
                  "composite", nboot=50) ##??
plot_inc(fit4, ylim=c(0,1),
         plot.configs=list(lty=2, lwd=3, main="My title"))