Visualise the top concepts per each cdm name, cohort, statification and window.

Usage

tableTopLargeScaleCharacteristics(
  result,
  topConcepts = 10,
  type = "gt",
  style = "default"
)

Arguments

result: A summarised_result object.
topConcepts: Number of concepts to restrict the table.
type: Type of table, it can be any of the supported visOmopResults::tableType() formats.
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().

Value

A formated table.

Examples

if (FALSE) { # \dontrun{
library(CohortCharacteristics)
library(omock)
libarry(CDMConnector)
library(dplyr, warn.conflicts = FALSE)

cdm <- mockCdmFromDataset(datasetName = "GiBleed", source = "duckdb")

cdm <- generateConceptCohortSet(
  cdm = cdm,
  conceptSet = list(viral_pharyngitis = 4112343),
  name = "my_cohort"
)

result <- summariseLargeScaleCharacteristics(
  cohort = cdm$my_cohort,
  window = list(c(-Inf, -1), c(0, 0), c(1, Inf)),
  episodeInWindow = "drug_exposure"
)

tableTopLargeScaleCharacteristics(result)

cdmDisconnect(cdm)
} # }