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[Experimental]

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

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",
  facet = c("cdm_name", "cohort_name_reference"),
  colour = c("cohort_name_comparator")
)

cdmDisconnect(cdm)
} # }