autoplot.predictCSC: Plot Predictions From a Cause-specific Cox Proportional...

In riskRegression: Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks

Plot Predictions From a Cause-specific Cox Proportional Hazard Regression

Description

Plot predictions from a Cause-specific Cox proportional hazard regression.

Usage

## S3 method for class 'predictCSC'
autoplot(
  object,
  ci = object$se,
  band = object$band,
  plot = TRUE,
  smooth = FALSE,
  digits = 2,
  alpha = NA,
  group.by = "row",
  reduce.data = FALSE,
  ...
)

Arguments

object	Object obtained with the function predictCox.
ci	[logical] If TRUE display the confidence intervals for the predictions.
band	[logical] If TRUE display the confidence bands for the predictions.
plot	[logical] Should the graphic be plotted.
smooth	[logical] Should a smooth version of the risk function be plotted instead of a simple function?
digits	[integer] Number of decimal places.
alpha	[numeric, 0-1] Transparency of the confidence bands. Argument passed to ggplot2::geom_ribbon.
group.by	[character] The grouping factor used to color the prediction curves. Can be "row", "strata", or "covariates".
reduce.data	[logical] If TRUE only the covariates that does take indentical values for all observations are displayed.
...	Additional parameters to cutomize the display.

Value

Invisible. A list containing:

• plot: the ggplot object.

• data: the data used to create the plot.

See Also

predict.CauseSpecificCox to compute risks based on a CSC model.

Examples

library(survival)
library(rms)
library(ggplot2)
library(prodlim)

#### simulate data ####
set.seed(10)
d <- sampleData(1e2, outcome = "competing.risks")
seqTau <- c(0,unique(sort(d[d$event==1,time])), max(d$time))

#### CSC model ####
m.CSC <- CSC(Hist(time,event)~ X1 + X2 + X6, data = d)

pred.CSC <- predict(m.CSC, newdata = d[1:2,], time = seqTau, cause = 1, band = TRUE)
autoplot(pred.CSC, alpha = 0.2)

#### stratified CSC model ####
m.SCSC <- CSC(Hist(time,event)~ strata(X1) + strata(X2) + X6,
              data = d)
pred.SCSC <- predict(m.SCSC, time = seqTau, newdata = d[1:4,],
                     cause = 1, keep.newdata = TRUE, keep.strata = TRUE)
autoplot(pred.SCSC, group.by = "strata")

riskRegression documentation built on Sept. 8, 2023, 6:12 p.m.