CohortCharacteristics (version 1.1.1)

summariseLargeScaleCharacteristics: This function is used to summarise the large scale characteristics of a cohort table

Description

This function is used to summarise the large scale characteristics of a cohort table

Usage

summariseLargeScaleCharacteristics(
  cohort,
  cohortId = NULL,
  strata = list(),
  window = list(c(-Inf, -366), c(-365, -31), c(-30, -1), c(0, 0), c(1, 30), c(31, 365),
    c(366, Inf)),
  eventInWindow = NULL,
  episodeInWindow = NULL,
  indexDate = "cohort_start_date",
  censorDate = NULL,
  includeSource = FALSE,
  minimumFrequency = 0.005,
  excludedCodes = c(0)
)

Value

The output of this function is a ResultSummary containing the relevant information.

Arguments

cohort

A cohort_table object.

cohortId

A cohort definition id to restrict by. If NULL, all cohorts will be included.

strata

A list of variables to stratify results. These variables must have been added as additional columns in the cohort table.

window

Temporal windows that we want to characterize.

eventInWindow

Tables to characterise the events in the window. eventInWindow must be provided if episodeInWindow is not specified.

episodeInWindow

Tables to characterise the episodes in the window. episodeInWindow must be provided if eventInWindow is not specified.

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

includeSource

Whether to include source concepts.

minimumFrequency

Minimum frequency of codes to be reported. If a concept_id has a frequency smaller than minimumFrequency in a certain window that estimate will be eliminated from the result object.

excludedCodes

Codes excluded.

Examples

if (FALSE) {
library(CohortCharacteristics)
library(DrugUtilisation)
library(dplyr, warn.conflicts = FALSE)
library(omock)

cdm <- mockCdmFromDataset(datasetName = "GiBleed", source = "duckdb")

cdm <- generateIngredientCohortSet(
  cdm = cdm, name = "my_cohort", ingredient = "acetaminophen"
)

cdm$my_cohort |>
  summariseLargeScaleCharacteristics(
    window = list(c(-365, -1), c(1, 365)),
    eventInWindow = "condition_occurrence"
  ) |>
  glimpse()

cdmDisconnect(cdm)
}