Make predictions for time-to-event outcomes at specified horizon times

Usage

# S4 method for class 'LandmarkAnalysis'
predict_survival(
  x,
  landmarks,
  horizons,
  method = "survfit",
  dynamic_covariates = c(),
  include_clusters = FALSE,
  censor_at_horizon = FALSE,
  validation_fold = 0,
  ...
)

Arguments

x: An object of class LandmarkAnalysis.
landmarks: Numeric vector of landmark times.
horizons: Vector of prediction horizons up to when the survival submodel is fitted.
method: Name of the function that is used to make predictions. At the moment, 'survfit' is the only supported @method.
dynamic_covariates: Vector of time-varying covariates to be used in the survival model.
include_clusters: Boolean indicating whether to propagate cluster membership to survival analysis.
censor_at_horizon: Boolean indicating whether to censor observations at horizon times
validation_fold: If positive, cross-validation fold where model is fitted. If 0 (default), model fitting is performed on the complete dataset.
...: Additional arguments passed to the prediction function (e.g. number of classes/clusters for lcmm).

Value

An object of class LandmarkAnalysis.