tableCohortTiming: Format a summariseCohortTiming result into a visual table.

In CohortCharacteristics: Summarise and Visualise Characteristics of Patients in the OMOP CDM

Format a summariseCohortTiming result into a visual table.

Description

Usage

tableCohortTiming(
  result,
  timeScale = "days",
  uniqueCombinations = TRUE,
  type = "gt",
  header = visOmopResults::strataColumns(result),
  groupColumn = NULL,
  hide = "variable_level"
)

Arguments

result	A summarised_result object. Output of summariseCohortTiming().
timeScale	Time scale to plot results. Can be days or years.
uniqueCombinations	Whether to restrict to unique reference and comparator comparisons.
type	Type of table. Check supported types with visOmopResults::tableType().
header	Columns to use as header. See options with tidyColumns(result).
groupColumn	Columns to group by. See options with tidyColumns(result).
hide	Columns to hide from the visualisation. See options with tidyColumns(result).

Value

A formatted table of the summariseCohortTiming result.

Examples

## Not run: 
library(CohortCharacteristics)
library(duckdb)
library(CDMConnector)
library(DrugUtilisation)

con <- dbConnect(duckdb(), eunomiaDir())
cdm <- cdmFromCon(con, cdmSchem = "main", writeSchema = "main")

cdm <- generateIngredientCohortSet(
  cdm = cdm,
  name = "my_cohort",
  ingredient = c("acetaminophen", "morphine", "warfarin")
)

timings <- summariseCohortTiming(cdm$my_cohort)

plotCohortTiming(
  timings,
  timeScale = "years",
  facet = c("cdm_name", "cohort_name_reference"),
  colour = c("cohort_name_comparator")
)

cdmDisconnect(cdm)

## End(Not run)

CohortCharacteristics documentation built on Oct. 1, 2024, 5:08 p.m.