summariseResult: Summarise variables using a set of estimate functions. The...

In PatientProfiles: Identify Characteristics of Patients in the OMOP Common Data Model

Summarise variables using a set of estimate functions. The output will be a formatted summarised_result object.

Description

Summarise variables using a set of estimate functions. The output will be a formatted summarised_result object.

Usage

summariseResult(
  table,
  group = list(),
  includeOverallGroup = FALSE,
  strata = list(),
  includeOverallStrata = TRUE,
  variables = NULL,
  estimates = c("min", "q25", "median", "q75", "max", "count", "percentage"),
  counts = TRUE,
  weights = NULL
)

Arguments

table	Table with different records.
group	List of groups to be considered.
includeOverallGroup	TRUE or FALSE. If TRUE, results for an overall group will be reported when a list of groups has been specified.
strata	List of the stratifications within each group to be considered.
includeOverallStrata	TRUE or FALSE. If TRUE, results for an overall strata will be reported when a list of strata has been specified.
variables	Variables to summarise, it can be a list to point to different set of estimate names.
estimates	Estimates to obtain, it can be a list to point to different set of variables.
counts	Whether to compute number of records and number of subjects.
weights	Name of the column in the table that contains the weights to be used when measuring the estimates.

Value

A summarised_result object with the summarised data of interest.

Examples

library(PatientProfiles)
library(dplyr)

cdm <- mockPatientProfiles()
x <- cdm$cohort1 |>
  addDemographics() |>
  collect()
result <- summariseResult(x)
mockDisconnect(cdm = cdm)

PatientProfiles documentation built on Aug. 8, 2025, 7:26 p.m.