Plot summariseMeasurementTiming results.

Usage

plotMeasurementSummary(
  result,
  x = "codelist_name",
  y = "days_between_measurements",
  plotType = "boxplot",
  facet = visOmopResults::strataColumns(result),
  colour = c("codelist_name"),
  style = NULL
)

Arguments

result: A summarised_result object.
x: Variable to plot on the x axis when plotType is "boxlot" or "barplot".
y: Variable to plot, it can be "days_between_measurements" or "measurements_per_subject".
plotType: Type of plot, either "boxplot", "barplot", or "densityplot".
facet: Columns to facet by. See options with `visOmopResults::plotColumns(result)`. Formula input is also allowed to specify rows and columns.
colour: Columns to color by. See options with `visOmopResults::plotColumns(result)`.
style: Pre-defined style to apply: "default" or "darwin" - the latter just for gt and flextable. If NULL the "default" style is used.

Value

A ggplot.

Examples

# \donttest{
library(MeasurementDiagnostics)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

cdm <- mockMeasurementDiagnostics()

result <- summariseMeasurementUse(
  cdm = cdm,
  codes = list("test_codelist" = c(3001467L, 45875977L))
)
#> → Sampling measurement table to 20000 subjects
#> → Getting measurement records based on 2 concepts.
#> → Subsetting records to the subjects and timing of interest.
#> → Getting time between records per person.
#> Summarising timings
#> ℹ The following estimates will be calculated:
#> • days_between_measurements: min, q25, median, q75, max, density
#> ! Table is collected to memory as not all requested estimates are supported on
#>   the database side
#> → Start summary of data, at 2026-02-09 16:09:19.477083
#> ✔ Summary finished, at 2026-02-09 16:09:19.582532
#> → Getting measurements per subject.
#> ℹ The following estimates will be calculated:
#> • measurements_per_subject: min, q25, median, q75, max, density
#> ! Table is collected to memory as not all requested estimates are supported on
#>   the database side
#> → Start summary of data, at 2026-02-09 16:09:20.173089
#> ✔ Summary finished, at 2026-02-09 16:09:20.266073
#> → Summarising results - value as number.
#> Summarising value as number
#> ℹ The following estimates will be calculated:
#> • value_as_number: min, q01, q05, q25, median, q75, q95, q99, max,
#>   count_missing, percentage_missing, density
#> ! Table is collected to memory as not all requested estimates are supported on
#>   the database side
#> → Start summary of data, at 2026-02-09 16:09:21.957218
#> ✔ Summary finished, at 2026-02-09 16:09:22.238771
#> → Summarising results - value as concept.
#> Summarising value as number
#> ℹ The following estimates will be calculated:
#> • value_as_concept_id: count, percentage
#> → Start summary of data, at 2026-02-09 16:09:22.95516
#> ✔ Summary finished, at 2026-02-09 16:09:23.109221
#> → Binding all diagnostic results.

result |>
  filter(variable_name == "days_between_measurements") |>
  plotMeasurementSummary()


CDMConnector::cdmDisconnect(cdm)
# }