Plot Survival Curves from Cox Model Data — cox_plot

Visualizes survival information using different representations (events, cumulative hazard, or survival percentage) for exposure groups based on a precomputed survival object.

Usage

cox_plot_overall(
  data,
  type = c("event", "cumhaz", "pct"),
  colors_exposure_groups = c("#5BC0DE", "#D9534F"),
  legend_labels = c("No exposure", "Exposure"),
  conf_int = TRUE,
  risk_table = FALSE
)

Arguments

data: A data frame containing the survival object (e.g., `Surv`) and exposure variable. The survival object must already be computed (typically by `cox_create_data()`), and the data should be ready for plotting.
type: Character string indicating the type of plot to generate. Options are: `"event"` for number of events over time, `"cumhaz"` for cumulative hazard, `"pct"` for survival percentage. Default is `"pct"`.
colors_exposure_groups: A character vector of color codes for the exposure groups. Default is Bootstrap-themed: `c("#5BC0DE", "#D9534F")`.
legend_labels: A character vector of labels for the exposure groups shown in the legend. Default is `c("No exposure", "Exposure")`.
conf_int: Logical. Whether to display confidence intervals (only applies if `type = "pct"`). Default is `TRUE`.
risk_table: Logical. Whether to include a risk table below the survival plot (only applies if `type = "pct"`). Default is `FALSE`.

Value

A `ggsurvplot` object, which can be printed or further modified with `ggplot2` functions.

Details

The function expects the input data to already include a survival object named `Surv`, such as one created via `Surv(tstart, tstop, diagnose)` within `cox_create_data()`. The exposure variable should also be present and appropriately formatted.

Examples

if (FALSE) { # \dontrun{
plot <- cox_plot_overall(
  data = cox_base,
  type = "pct",
  colors_exposure_groups = c("#5BC0DE", "#D9534F"),
  legend_labels = c("No exposure", "Exposure"),
  conf_int = TRUE,
  risk_table = TRUE
)
print(plot)
} # }