Wrapper for Survival Regression Trees (rpart)

Final Production Wrapper for single decision trees. Uses rpart with method="exp" and calculates survival probabilities using the Breslow estimator.

Usage

surv.rpart(
  time,
  event,
  X,
  newdata,
  new.times,
  obsWeights,
  id,
  cp = 0.01,
  minsplit = 20,
  maxdepth = 30,
  ...
)

Arguments

time: Observed follow-up time.
event: Observed event indicator.
X: Training covariate data.frame.
newdata: Test covariate data.frame to use for prediction.
new.times: Times at which to obtain predicted survivals.
obsWeights: Observation weights.
id: Optional cluster/individual ID indicator.
cp: Complexity parameter (default: 0.01).
minsplit: Minimum number of observations to attempt a split (default: 20).
maxdepth: Maximum depth of any node of the final tree (default: 30).
...: Additional arguments passed to rpart.control.

Value

A list containing:

fit: The fitted model object (e.g., the raw coxph or xgb.Booster object). If the model fails to fit, this may be an object of class try-error.
pred: A numeric matrix of cross-validated survival predictions evaluated at the specified new.times grid.

Examples

if (requireNamespace("rpart", quietly = TRUE)) {
  data("metabric", package = "SuperSurv")
  dat <- metabric[1:30, ]
  x_cols <- grep("^x", names(dat))[1:3]
  X <- dat[, x_cols, drop = FALSE]
  newX <- X[1:5, , drop = FALSE]
  times <- seq(50, 150, by = 50)

  fit <- surv.rpart(
    time = dat$duration,
    event = dat$event,
    X = X,
    newdata = newX,
    new.times = times,
    obsWeights = rep(1, nrow(dat)),
    id = NULL,
    cp = 0.01,
    minsplit = 5,
    maxdepth = 3
  )

  dim(fit$pred)
}
#> [1] 5 3