clinpubr (version 1.1.1)

time_roc_plot: Calculate and plot time-dependent ROC curves

Description

Calculate time-dependent ROC curves using the timeROC package and plot them using ggplot2.

Usage

time_roc_plot(
  data,
  time_var,
  event_var,
  marker_var,
  times = c(12, 36, 60),
  weighting = "marginal",
  cause = 1,
  colors = NULL,
  title = FALSE,
  save_plot = FALSE,
  filename = "time_roc.png"
)

Value

A list containing:

• time_roc: The timeROC result object.

• plot: A ggplot object of the time-dependent ROC curves.

Arguments

data

A data frame containing the survival time, event indicator, and marker variable.

time_var

A string specifying the name of the survival time variable in the data frame.

event_var

A string specifying the name of the event indicator variable in the data frame.

marker_var

A string specifying the name of the marker variable in the data frame.

times

A numeric vector of times at which to compute the time-dependent ROC curves.

weighting

A character string specifying the weighting method. Default is "marginal". See timeROC::timeROC() for details.

cause

The value of the event indicator that denotes the event of interest. Default is 1.

colors

A vector of colors to use for the ROC curves. If NULL, uses default colors.

title

A logical value indicating whether to include a title. Default is FALSE.

save_plot

A logical value indicating whether to save the plot to a file. Default is FALSE.

filename

A string specifying the filename to save the plot. Default is "time_roc.png".

Examples

# Plot time-dependent ROC curves using lung dataset from survival package
library(survival)
data(cancer, package = "survival")
# Use age as the marker variable, plot at 6, 12, and 24 months
lung$status <- lung$status == 2
result <- time_roc_plot(lung, "time", "status", "age", times = c(180, 365, 730))
result$plot

# Save the plot to a file
# time_roc_plot(lung, "time", "status", "age", times = c(180, 365, 730), save_plot = TRUE)