Predict method for SuperSurv fits — predict.SuperSurv • SuperSurv

Obtains predicted survival probabilities from a fitted SuperSurv ensemble.

Usage

# S3 method for class 'SuperSurv'
predict(
  object,
  newdata,
  new.times,
  type = c("both", "event", "censoring"),
  onlySL = FALSE,
  threshold = 1e-04,
  ...
)

Arguments

object: A fitted object of class SuperSurv.
newdata: A data.frame of new covariate values.
new.times: A numeric vector of times at which to predict survival.
type: Character string specifying the prediction output. Use "event" for the event survival matrix, "censoring" for the censoring survival matrix, or "both" for the full list of outputs.
onlySL: Logical. If TRUE, only uses models with weights > threshold.
threshold: Numeric. The weight threshold for onlySL.
...: Additional ignored arguments.

Value

If type = "event" or type = "censoring", a numeric matrix with rows corresponding to observations and columns corresponding to new.times. If type = "both", a list containing:

event.predict: A numeric matrix of final event survival predictions.
event.library.predict: A 3D numeric array of event learner predictions.
cens.predict: A numeric matrix of final censoring survival predictions.
cens.library.predict: A 3D numeric array of censoring learner predictions.

Examples

if (requireNamespace("glmnet", quietly = TRUE)) {
  data("metabric", package = "SuperSurv")
  dat <- metabric[1:80, ]
  x_cols <- grep("^x", names(dat))[1:5]
  X <- dat[, x_cols, drop = FALSE]
  newX <- X[1:10, , drop = FALSE]
  new.times <- seq(20, 120, by = 20)

  fit <- SuperSurv(
    time = dat$duration,
    event = dat$event,
    X = X,
    newdata = X,
    new.times = new.times,
    event.library = c("surv.coxph", "surv.ridge"),
    cens.library = c("surv.coxph"),
    control = list(saveFitLibrary = TRUE)
  )

  pred_event <- predict(
    object = fit,
    newdata = newX,
    new.times = new.times,
    type = "event"
  )

  dim(pred_event)
}
#> [1] 10  6