vim_cindex function

Estimate concordance index VIM

vim_cindex(
  time,
  event,
  approx_times,
  restriction_time,
  f_hat,
  fs_hat,
  S_hat,
  G_hat,
  cf_folds,
  sample_split,
  ss_folds,
  scale_est = FALSE,
  alpha = 0.05
)

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. Defaults to a vector of 1s, i.e. no censoring.
• approx_times: Numeric vector of length J1 giving times at which to approximate integrals.
• restriction_time: Restriction time (upper bound for event times to be compared in computing the C-index)
• f_hat: Full oracle predictions (n x J1 matrix)
• fs_hat: Residual oracle predictions (n x J1 matrix)
• S_hat: Estimates of conditional event time survival function (n x J2 matrix)
• G_hat: Estimate of conditional censoring time survival function (n x J2 matrix)
• cf_folds: Numeric vector of length n giving cross-fitting folds
• sample_split: Logical indicating whether or not to sample split
• ss_folds: Numeric vector of length n giving sample-splitting folds
• scale_est: Logical, whether or not to force the VIM estimate to be nonnegative
• alpha: The level at which to compute confidence intervals and hypothesis tests. Defaults to 0.05

Returns

A data frame giving results, with the following columns: - restriction_time: Restriction time (upper bound for event times to be compared in computing the C-index).

• est: VIM point estimate.

• var_est: Estimated variance of the VIM estimate.

• cil: Lower bound of the VIM confidence interval.

• ciu: Upper bound of the VIM confidence interval.

• cil_1sided: Lower bound of a one-sided confidence interval.

• p: p-value corresponding to a hypothesis test of null importance.

• large_predictiveness: Estimated predictiveness of the large oracle prediction function.

• small_predictiveness: Estimated predictiveness of the small oracle prediction function.

• vim: VIM type.

• large_feature_vector: Group of features available for the large oracle prediction function.

• small_feature_vector: Group of features available for the small oracle prediction function.

See Also

vim for example usage