This function is used to add columns with the large scale characteristics of a cohort table. — addLargeScaleCharacteristics • PatientProfiles

`r lifecycle::badge("experimental")`

Usage

addLargeScaleCharacteristics(
  cohort,
  window = list(c(0, Inf)),
  eventInWindow = NULL,
  episodeInWindow = NULL,
  indexDate = "cohort_start_date",
  censorDate = NULL,
  minimumFrequency = 0.005,
  excludedCodes = NULL
)

Arguments

cohort: The cohort to characterise.
window: Temporal windows that we want to characterize.
eventInWindow: Tables to characterise the events in the window.
episodeInWindow: Tables to characterise the episodes in the window.
indexDate: Variable in x that contains the date to compute the intersection.
censorDate: whether to censor overlap events at a specific date or a column date of x.
minimumFrequency: Minimum frequency covariates to report.
excludedCodes: Codes excluded.

Value

The output of this function is the cohort with the new created columns.

Examples

# \donttest{
library(PatientProfiles)
cdm <- PatientProfiles::mockPatientProfiles()
results <- cdm$cohort2 %>%
  addLargeScaleCharacteristics(
  episodeInWindow = c("condition_occurrence"),
  minimumFrequency = 0
  )
CDMConnector::cdmDisconnect(cdm = cdm)
# }