Simulates an artifical EHR-derived analysis-ready oncology dataset

Parameterized function to quickly create an EHR-derived analytic cohort for analytic code development.

Usage

simulate_data(
  n_total = 3500,
  seed = 42,
  include_id = TRUE,
  imposeNA = TRUE,
  propNA = NULL
)

Arguments

n_total

integer, number of total patients

seed

integer, seed for reproducibility

include_id

logical, include a generated patientid variable

imposeNA

logical, set covariates to missing

propNA

numeric, proportion of missingness, needs to be between 0 and 1

Value

data frame with simulated analytic cohort

Details

This function simulates a cohort of patients with oncology data. The cohort is simulated using a Weibull distribution for time to event and a logistic distribution for treatment assignment. The function also allows for missingness to be imposed on the data. The function is parameterized to allow for the number of patients to be simulated, the seed for reproducibility, and whether to include a patient id variable.

Examples

if (FALSE) { # \dontrun{
library(encore.analytics)

# Original uniform missingness
data_uniform <- simulate_data(
  n_total = 3500,
  seed = 41,
  include_id = FALSE,
  imposeNA = TRUE,
  propNA = .33
  )

# Now creates variable missingness across columns with average of 0.33
data_variable <- simulate_data(
  n_total = 3500,
  seed = 41,
  include_id = FALSE,
  imposeNA = TRUE,
  propNA = .33
  )

head(data_variable)

} # }