step_expose: Create exposure records in a `recipes` step

Description

step_expose() creates a specification of a recipe step that will convert a data frame of census-level records to exposure-level records.

Usage

step_expose(
  recipe,
  ...,
  role = NA,
  trained = FALSE,
  end_date,
  start_date = as.Date("1900-01-01"),
  target_status = NULL,
  options = list(cal_expo = FALSE, expo_length = "year"),
  drop_pol_num = TRUE,
  skip = TRUE,
  id = recipes::rand_id("expose")
)

Value

An updated version of recipe with the new expose step added to the sequence of any existing operations. For the tidy method, a tibble with the columns exposure_type, target_status, start_date, and end_date.

Arguments

recipe: A recipe object. The step will be added to the sequence of operations for this recipe.
...: One or more selector functions to choose variables for this step. See selections() for more details.
role: Not used by this step since no new variables are created.
trained: A logical to indicate if the quantities for preprocessing have been estimated.
end_date: Experience study end date
start_date: Experience study start date. Default value = 1900-01-01.
target_status: Character vector of target status values. Default value = NULL.
options: A named list of additional arguments passed to expose().
drop_pol_num: Whether the pol_num column produced by expose() should be dropped. Defaults to TRUE.
skip: A logical. Should the step be skipped when the recipe is baked by bake()? While all operations are baked when prep() is run, some operations may not be able to be conducted on new data (e.g. processing the outcome variable(s)). Care should be taken when using skip = TRUE as it may affect the computations for subsequent operations.
id: A character string that is unique to this step to identify it.

Details

Policy year exposures are calculated as a default. To switch to calendar exposures or another exposure length, use pass the appropriate arguments to the options parameter.

Policy numbers are dropped as a default whenever the recipe is baked. This is done to prevent unintentional errors when the model formula includes all variables (y ~ .). If policy numbers are required for any reason (mixed effect models, identification, etc.), set drop_pol_num to FALSE.

Examples

Run this code


expo_rec <- recipes::recipe(status ~ ., toy_census) |>
  step_expose(end_date = "2022-12-31", target_status = "Surrender",
              options = list(expo_length = "month")) |>
  prep()

recipes::juice(expo_rec)