plotCharacteristics: Create a ggplot from the output of summariseCharacteristics.

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

Create a ggplot from the output of summariseCharacteristics.

Description

Usage

plotCharacteristics(
  result,
  plotType = "barplot",
  facet = NULL,
  colour = NULL,
  plotStyle = lifecycle::deprecated()
)

Arguments

result	A summarised_result object.
plotType	Either barplot, scatterplot or boxplot. If barplot or scatterplot subset to just one estimate.
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).
plotStyle	deprecated.

Value

A ggplot.

Examples

library(CohortCharacteristics)
library(dplyr, warn.conflicts = FALSE)

cdm <- mockCohortCharacteristics()

results <- summariseCharacteristics(
  cohort = cdm$cohort1,
  ageGroup = list(c(0, 19), c(20, 39), c(40, 59), c(60, 79), c(80, 150)),
  tableIntersectCount = list(
    tableName = "visit_occurrence", window = c(-365, -1)
  ),
  cohortIntersectFlag = list(
    targetCohortTable = "cohort2", window = c(-365, -1)
  )
)

results |>
  filter(
    variable_name == "Cohort2 flag -365 to -1", estimate_name == "percentage"
  ) |>
  plotCharacteristics(
    plotType = "barplot",
    colour = "variable_level",
    facet = c("cdm_name", "cohort_name")
  )

results |>
  filter(variable_name == "Age", estimate_name == "mean") |>
  plotCharacteristics(
    plotType = "scatterplot",
    facet = "cdm_name"
  )

results |>
  filter(variable_name == "Age", group_level == "cohort_1") |>
  plotCharacteristics(
    plotType = "boxplot",
    facet = "cdm_name",
    colour = "cohort_name"
  )

mockDisconnect(cdm)

CohortCharacteristics documentation built on April 3, 2025, 10:29 p.m.