Format a summarise_characteristics object into a visual table.

Usage

tableCharacteristics(
  result,
  type = NULL,
  header = c("cdm_name", "cohort_name"),
  groupColumn = character(),
  hide = c(additionalColumns(result), settingsColumns(result)),
  style = NULL,
  .options = list()
)

Arguments

result

A summarised_result object.

type

Character string specifying the desired output table format. See visOmopResults::tableType() for supported table types. If type = NULL, global options (set via visOmopResults::setGlobalTableOptions()) will be used if available; otherwise, a default 'gt' table is created.

header

Columns to use as header. See options with availableTableColumns(result).

groupColumn

Columns to group by. See options with availableTableColumns(result).

hide

Columns to hide from the visualisation. See options with availableTableColumns(result).

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

1. Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See visOmopResults::tableStyle() for available options.

2. YAML file path: Provide the path to an existing .yml file defining a new style.

3. List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type.

If style = NULL, the function will use global options (see visOmopResults::setGlobalTableOptions()) or an existing _brand.yml file (if found); otherwise, the default style is applied. For more details, see the Styles vignette in visOmopResults website.

.options

A named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A formatted table.

Examples

# \donttest{
library(CohortCharacteristics)

cdm <- mockCohortCharacteristics()
#> Warning: There are observation period end dates after the current date: 2026-01-28
#> ℹ The latest max observation period end date found is 2030-07-06

result <- summariseCharacteristics(cdm$cohort1)
#> ℹ adding demographics columns
#> ℹ summarising data
#> ℹ summarising cohort cohort_1
#> ℹ summarising cohort cohort_2
#> ℹ summarising cohort cohort_3
#> ✔ summariseCharacteristics finished!

tableCharacteristics(result)


  

      

        
CDM name
      
    

      

        
PP_MOCK
      
    
Variable name
      
Variable level
      
Estimate name
      

        
Cohort name
      
    
cohort_1
      
cohort_2
      
cohort_3
    
Number records
–
N
4
3
3
Number subjects
–
N
4
3
3
Cohort start date
–
Median [Q25 - Q75]
1956-03-13 [1934-06-15 - 1983-10-06]
1980-10-23 [1945-11-16 - 1985-12-18]
1932-12-15 [1924-12-14 - 1937-04-05]


Range
1932-01-19 to 2003-08-17
1910-12-10 to 1991-02-12
1916-12-12 to 1941-07-25
Cohort end date
–
Median [Q25 - Q75]
1960-05-09 [1935-12-13 - 1992-12-27]
1985-09-18 [1949-02-26 - 1988-06-17]
1934-12-20 [1926-07-11 - 1940-10-02]


Range
1935-02-09 to 2018-07-05
1912-08-07 to 1991-03-16
1918-01-29 to 1946-07-16
Age
–
Median [Q25 - Q75]
12 [8 - 17]
23 [13 - 30]
11 [8 - 16]


Mean (SD)
12.75 (10.69)
21.33 (17.56)
12.33 (9.07)


Range
0 to 26
3 to 38
4 to 22
Sex
Female
N (%)
2 (50.00%)
1 (33.33%)
3 (100.00%)

Male
N (%)
2 (50.00%)
2 (66.67%)
–
Prior observation
–
Median [Q25 - Q75]
4,621 [3,096 - 6,279]
8,696 [5,068 - 11,308]
4,363 [3,014 - 6,374]


Mean (SD)
4,754.00 (3,974.25)
8,018.67 (6,268.51)
4,804.33 (3,380.67)


Range
50 to 9,724
1,439 to 13,921
1,666 to 8,384
Future observation
–
Median [Q25 - Q75]
6,548 [2,965 - 9,649]
2,478 [1,309 - 3,920]
2,078 [1,409 - 2,210]


Mean (SD)
6,065.25 (4,296.56)
2,659.67 (2,615.24)
1,720.00 (858.91)


Range
1,344 to 9,820
140 to 5,361
740 to 2,342
Days in cohort
–
Median [Q25 - Q75]
1,900 [928 - 3,372]
607 [320 - 1,200]
736 [575 - 1,277]


Mean (SD)
2,398.50 (2,245.36)
810.67 (897.01)
989.33 (735.48)


Range
356 to 5,437
33 to 1,792
414 to 1,818
Days to next record
–
Median [Q25 - Q75]
–
–
–


Mean (SD)
–
–
–


Range
–
–
–

# }