CohortCharacteristics (version 1.1.1)

summariseCharacteristics: Summarise characteristics of cohorts in a cohort table

Description

Summarise characteristics of cohorts in a cohort table

Usage

summariseCharacteristics(
  cohort,
  cohortId = NULL,
  strata = list(),
  counts = TRUE,
  demographics = TRUE,
  ageGroup = NULL,
  tableIntersectFlag = list(),
  tableIntersectCount = list(),
  tableIntersectDate = list(),
  tableIntersectDays = list(),
  cohortIntersectFlag = list(),
  cohortIntersectCount = list(),
  cohortIntersectDate = list(),
  cohortIntersectDays = list(),
  conceptIntersectFlag = list(),
  conceptIntersectCount = list(),
  conceptIntersectDate = list(),
  conceptIntersectDays = list(),
  otherVariables = character(),
  estimates = list(),
  weights = NULL
)

Value

A summary of the characteristics of the cohorts in the cohort table.

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.

counts

TRUE or FALSE. If TRUE, record and person counts will be produced.

demographics

TRUE or FALSE. If TRUE, patient demographics (cohort start date, cohort end date, age, sex, prior observation, and future observation will be summarised).

ageGroup

A list of age groups to stratify results by.

tableIntersectFlag

A list of arguments that uses PatientProfiles::addTableIntersectFlag() to add variables to summarise.

tableIntersectCount

A list of arguments that uses PatientProfiles::addTableIntersectCount() to add variables to summarise.

tableIntersectDate

A list of arguments that uses PatientProfiles::addTableIntersectDate() to add variables to summarise.

tableIntersectDays

A list of arguments that uses PatientProfiles::addTableIntersectDays() to add variables to summarise.

cohortIntersectFlag

A list of arguments that uses PatientProfiles::addCohortIntersectFlag() to add variables to summarise.

cohortIntersectCount

A list of arguments that uses PatientProfiles::addCohortIntersectCount() to add variables to summarise.

cohortIntersectDate

A list of arguments that uses PatientProfiles::addCohortIntersectDate() to add variables to summarise.

cohortIntersectDays

A list of arguments that uses PatientProfiles::addCohortIntersectDays() to add variables to summarise.

conceptIntersectFlag

A list of arguments that uses PatientProfiles::addConceptIntersectFlag() to add variables to summarise.

conceptIntersectCount

A list of arguments that uses PatientProfiles::addConceptIntersectCount() to add variables to summarise.

conceptIntersectDate

A list of arguments that uses PatientProfiles::addConceptIntersectDate() to add variables to summarise.

conceptIntersectDays

A list of arguments that uses PatientProfiles::addConceptIntersectDays() to add variables to summarise.

otherVariables

Other variables contained in cohort that you want to be summarised.

estimates

To modify the default estimates for a variable. By default: 'min', 'q25', 'median', 'q75', 'max' for "date", for "numeric" and "integer" variables ("numeric" and "integer" also use 'mean' and 'sd' estimates). 'count' and 'percentage' for "categorical" and "binary". You have to provide them as a list: list(age = c("median", "density")). You can also use 'date', 'numeric', 'integer', 'binary', 'categorical', 'demographics', 'intersect', 'other', 'table_intersect_count', ... as valid labels, see available estimates using PatientProfiles::availableEstimates()

weights

Column in cohort that points to weights of each individual.

Examples

# \donttest{
library(dplyr, warn.conflicts = FALSE)
library(CohortCharacteristics)
library(PatientProfiles)

cdm <- mockCohortCharacteristics()

cdm$cohort1 |>
  addSex() |>
  addAge(
    ageGroup = list(c(0, 40), c(41, 150))
  ) |>
  summariseCharacteristics(
    strata = list("sex", "age_group"),
    cohortIntersectFlag = list(
      "Cohort 2 Flag" = list(
        targetCohortTable = "cohort2", window = c(-365, 0)
      )
    ),
    cohortIntersectCount = list(
      "Cohort 2 Count" = list(
        targetCohortTable = "cohort2", window = c(-365, 0)
      )
    )
  ) |>
  glimpse()

# }