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Estimate full oracle prediction function using DR pseudo-outcome regression

Source: R/prebuilt_generators.R
generate_oracle_predictions_DR.Rd

Estimate full oracle prediction function using DR pseudo-outcome regression

Usage

generate_oracle_predictions_DR(
  time,
  event,
  X,
  X_holdout,
  nuisance_preds,
  outcome,
  landmark_times,
  restriction_time,
  approx_times,
  SL.library = c("SL.mean", "SL.glm", "SL.earth", "SL.gam", "SL.ranger"),
  V = 5,
  indx
)

Arguments

time

n x 1 numeric vector of observed follow-up times. If there is censoring, these are the minimum of the event and censoring times.

event

n x 1 numeric vector of status indicators of whether an event was observed.

X

n x p data.frame of observed covariate values

X_holdout

m x p data.frame of new observed covariate values at which to obtain m predictions for the estimated algorithm. Must have the same names and structure as X.

nuisance_preds

Named list of conditional survival function predictions with elements "S_hat", "S_hat_train", "G_hat", and "G_hat_train". This should match the output of conditional_surv_generator.

outcome

Outcome type, either "survival_probability" or "restricted_survival_time"

landmark_times

Numeric vector of length J1 giving landmark times at which to estimate VIM ("accuracy", "AUC", "Brier", "R-squared").

restriction_time

Maximum follow-up time for calculation of "survival_time_MSE". Essentially, this time should be chosen such that the conditional survival function is identified at this time for all covariate values X present in the data. Choosing the restriction time such that roughly 10% of individuals remain at-risk at that time has been shown to work reasonably well in simulations.

approx_times

Numeric vector of length J2 giving times at which to approximate integral appearing in the pseudo-outcomes

SL.library

Super Learner library

V

Number of cross-validation folds, to be passed to SuperLearner

indx

Numeric index of column(s) of X to be removed, i.e., not used in the oracle prediction function.

Value

A list containing elements f0_hat and f0_hat_train, the estimated oracle prediction functions for X_holdout and X, respectively.

See also

DR_pseudo_outcome_regression