plotCohortTiming: Plot summariseCohortTiming results.

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

Plot summariseCohortTiming results.

Description

Usage

plotCohortTiming(
  result,
  plotType = "boxplot",
  timeScale = "days",
  uniqueCombinations = TRUE,
  facet = c("cdm_name", "cohort_name_reference"),
  colour = c("cohort_name_comparator")
)

Arguments

result	A summarised_result object. Output of summariseCohortTiming().
plotType	Type of desired formatted table, possibilities are "boxplot" and "density".
timeScale	Time scale to plot results. Can be days or years.
uniqueCombinations	Whether to restrict to unique reference and comparator comparisons.
facet	Columns to facet by. See options with tidyColumns(result). Formula is also allowed to specify rows and columns.
colour	Columns to color by. See options with tidyColumns(result).

Value

A ggplot.

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.