Format a summarise_large_scale_characteristics object into a visual table.

Usage

tableLargeScaleCharacteristics(
  result,
  topConcepts = NULL,
  type = "gt",
  header = c("cdm_name", "cohort_name", strataColumns(result), "variable_level"),
  groupColumn = c("table_name", "type", "analysis"),
  hide = character()
)

Arguments

result

A summarised_result object.

topConcepts

Number of concepts to restrict the table.

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).

Value

A formatted table.

Examples

if (FALSE) { # \dontrun{
library(duckdb)
library(CDMConnector)

con <- dbConnect(duckdb(), eunomiaDir())
cdm <- cdmFromCon(con = con, cdmSchema = "main", writeSchema = "main")
cdm <- generateConceptCohortSet(
  cdm = cdm,
  conceptSet = list("viral_pharyngitis" = 4112343),
  name = "my_cohort"
)

result <- summariseLargeScaleCharacteristics(
  cohort = cdm$my_cohort,
  eventInWindow = "condition_occurrence",
  episodeInWindow = "drug_exposure"
)

tableLargeScaleCharacteristics(result)

cdmDisconnect(cdm)
} # }