Format a summarise_characteristics object into a visual table.

Usage

tableCohortCount(
  result,
  type = "gt",
  header = "cohort_name",
  groupColumn = character(),
  hide = c("variable_level", settingsColumns(result)),
  style = "default",
  .options = list()
)

Arguments

result

A summarised_result object.

type

Type of table. Check supported types with visOmopResults::tableType().

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

Named list that specifies how to style the different parts of the table generated. It can either be a pre-defined style ("default" or "darwin" - the latter just for gt and flextable), NULL to get the table default style, or custom. Keep in mind that styling code is different for all table styles. To see the different styles see visOmopResults::tableStyle().

.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()

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

tableCohortCount(result)


  
CDM name
      
Variable name
      
Estimate name
      

        
Cohort name
      
    
cohort_1
      
cohort_2
      
cohort_3
    
PP_MOCK
Number records
N
3
2
5

Number subjects
N
3
2
5

# }