sig_roc: Plot ROC Curves and Compare Them

In IOBR: Immune Oncology Biological Research

Plot ROC Curves and Compare Them

Description

Generates Receiver Operating Characteristic (ROC) curves for multiple predictors and optionally performs statistical comparisons between them.

Usage

sig_roc(
  data,
  response,
  variables,
  fig.path = NULL,
  main = NULL,
  file.name = NULL,
  palette = "jama",
  cols = NULL,
  alpha = 1,
  compare = FALSE,
  smooth = TRUE,
  compare_method = "bootstrap",
  boot.n = 100
)

Arguments

data	Data frame containing the predictor variables and binary outcome.
response	Character. Name of the binary outcome variable in 'data'.
variables	Character vector. Names of predictor variables for ROC curves.
fig.path	Character or 'NULL'. Directory path to save output PDF. Default is 'NULL'.
main	Character or 'NULL'. Main title for the ROC plot. Default is 'NULL'.
file.name	Character or 'NULL'. Output PDF filename without extension. Default is '"0-ROC of multiple variables"'.
palette	Character. Color palette for ROC curves. Default is '"jama"'.
cols	Character vector or 'NULL'. Custom colors for ROC curves. Default is 'NULL'.
alpha	Numeric. Transparency level (1 = opaque, 0 = transparent). Default is '1'.
compare	Logical. Whether to perform statistical comparison of AUCs. Default is 'FALSE'.
smooth	Logical. Whether to smooth ROC curves. Default is 'TRUE'.
compare_method	Character. Method for comparing ROC curves. Default is '"bootstrap"'.
boot.n	Integer. Number of bootstrap replications. Default is '100'.

Value

A list containing:

auc.out

Data frame with AUC values and confidence intervals

legend.name

Vector of legend entries for the plot

p.out

If 'compare = TRUE', data frame with p-values from comparisons

Author(s)

Dongqiang Zeng

Examples

set.seed(123)
test_data <- data.frame(
  OS_status = sample(c(0, 1), 20, replace = TRUE),
  Marker1 = rnorm(20),
  Marker2 = rnorm(20)
)
result <- sig_roc(data = test_data, response = "OS_status",
                  variables = c("Marker1", "Marker2"),
                  smooth = FALSE)
if (!is.null(result)) print(result$auc.out)

IOBR documentation built on May 30, 2026, 5:07 p.m.