Summarise variables using a set of estimate functions. The output will be a formatted summarised_result object.
Source:R/summariseResult.R
summariseResult.Rd
Summarise variables using a set of estimate functions. The output will be a formatted summarised_result object.
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.
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 2024-11-09 18:00:10.369412
#> ✔ Summary finished, at 2024-11-09 18:00:10.447602
mockDisconnect(cdm = cdm)
# }