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
)

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.

Value

A summarised_result object with the summarised data of interest.

Examples

# \donttest{
library(PatientProfiles)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

cdm <- mockPatientProfiles()
x <- cdm$cohort1 |>
  addDemographics() |>
  collect()
result <- summariseResult(x)
#> ℹ The following estimates will be computed:
#> • cohort_start_date: min, q25, median, q75, max
#> • cohort_end_date: min, q25, median, q75, max
#> • age: min, q25, median, q75, max
#> • sex: count, percentage
#> • prior_observation: min, q25, median, q75, max
#> • future_observation: min, q25, median, q75, max
#> ! Table is collected to memory as not all requested estimates are supported on
#>   the database side
#> → Start summary of data, at 2024-12-19 13:11:11.216003
#> ✔ Summary finished, at 2024-12-19 13:11:11.291331
mockDisconnect(cdm = cdm)
# }