Fits a survival model using the censored/parsnip framework. The outcome must be specified as separate time and event columns (following survival::Surv() convention), and the user must explicitly choose an engine.

Fits a survival model using the censored/parsnip framework. The outcome must be specified as separate time and event columns (following survival::Surv() convention), and the user must explicitly choose an engine.

Usage

tr_fit_survival(
  data,
  time_col,
  event_col,
  engine = c("cox_ph", "survival_rf"),
  predictors = NULL
)

Arguments

data

A data frame containing predictors, a time column, and an event column.

time_col

Character. Name of the column giving time to event or censoring.

event_col

Character. Name of the column indicating event status (1 = event occurred, 0 = censored), following standard survival analysis convention.

engine

Character. One of "cox_ph" (Cox Proportional Hazards) or "survival_rf" (Random Survival Forest via the aorsf engine).

predictors

Character vector of predictor column names. If NULL (default), all columns except time_col and event_col are used.

Value

A fitted triageR_survival_model object (list) containing the fitted workflow, engine, and time/event/predictor column names.

Examples

if (requireNamespace("survival", quietly = TRUE)) {
  library(survival)
  lung_clean <- lung
  lung_clean$status <- lung_clean$status - 1  # convert 1/2 to 0/1
  lung_clean <- lung_clean[stats::complete.cases(lung_clean), ]
  model <- tr_fit_survival(lung_clean, time_col = "time",
                            event_col = "status", engine = "cox_ph")
}
#> Survival model fitted successfully using engine: cox_ph