A wrapper for survival probabilities with coxnet models

Usage

survival_prob_coxnet(
  object,
  new_data,
  eval_time,
  time = deprecated(),
  output = "surv",
  penalty = NULL,
  multi = FALSE,
  ...
)

Arguments

object: A parsnip model_fit object resulting from proportional_hazards() with engine = "glmnet".
new_data: Data for prediction.
eval_time: A vector of integers for prediction times.
time: Deprecated in favor of eval_time. A vector of integers for prediction times.
output: One of "surv" or "haz".
penalty: Penalty value(s).
multi: Allow multiple penalty values? Defaults to FALSE.
...: Options to pass to survival::survfit().

Value

A tibble with a list column of nested tibbles.

Examples

cox_mod <- proportional_hazards(penalty = 0.1) %>%
  set_engine("glmnet") %>%
  fit(Surv(time, status) ~ ., data = lung)
survival_prob_coxnet(cox_mod, new_data = lung[1:3, ], eval_time = 300)
#> # A tibble: 3 × 1
#>   .pred           
#>   <list>          
#> 1 <tibble [1 × 2]>
#> 2 <tibble [1 × 2]>
#> 3 <tibble [1 × 2]>