Create a ggplot2 plot from the output of summariseTrend()

Usage

plotTrend(result, output = NULL, facet = "type", colour = NULL, style = NULL)

Arguments

result

A summarised_result object (output of summariseTrend()).

output

The output to plot. Accepted values are: "record", "person", "person-days", "age", and "sex". If not specified, the function will default to:

the only available output if there is just one in the results, or
"record" if multiple outputs are present.

facet

Columns to face by. Formula format can be provided. See possible columns to face by with: visOmopResults::tidyColumns().

colour

Columns to colour by. See possible columns to colour by with: visOmopResults::tidyColumns().

style

Visual theme to apply. Character, or NULL. If a character, this may be either the name of a built-in style (see visOmopResults::plotStyle()), or a path to a .yml file that defines a custom style. If NULL, the function will use the explicit default style, unless a global style option is set (see visOmopResults::setGlobalPlotOptions()) or a _brand.yml file is present (in that order).

Value

A plot visualisation.

Examples

# \donttest{
library(dplyr)
library(OmopSketch)
library(omock)

cdm <- mockCdmFromDataset(datasetName = "GiBleed", source = "duckdb")
#> ℹ Reading GiBleed tables.
#> ℹ Adding drug_strength table.
#> ℹ Creating local <cdm_reference> object.
#> ℹ Inserting <cdm_reference> into duckdb.

result <- summariseTrend(cdm,
  episode = "observation_period",
  output = c("person-days", "record"),
  interval = "years",
  ageGroup = list("<=40" = c(0, 40), ">40" = c(41, Inf)),
  sex = TRUE
)

plotTrend(
  result = result,
  output = "record",
  colour = "sex",
  facet = "age_group"
)


cdmDisconnect(cdm = cdm)
# }