Plot summariseCohortTiming results.

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.

plotType

Type of desired formatted table, possibilities are "boxplot" and "densityplot".

timeScale

Time scale to show, it can be "days" or "years".

uniqueCombinations

Whether to restrict to unique reference and comparator comparisons.

facet

Columns to facet by. See options with availablePlotColumns(result). Formula is also allowed to specify rows and columns.

colour

Columns to color by. See options with availablePlotColumns(result).

Value

A ggplot.

Examples

if (FALSE) { # \dontrun{
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",
  uniqueCombinations = FALSE,
  facet = c("cdm_name", "cohort_name_reference"),
  colour = c("cohort_name_comparator")
)

plotCohortTiming(
  timings,
  plotType = "densityplot",
  timeScale = "years",
  uniqueCombinations = FALSE,
  facet = c("cdm_name", "cohort_name_reference"),
  colour = c("cohort_name_comparator")
)

cdmDisconnect(cdm)
} # }