Skip to contents

Format a measurement_summary object into a visual table

Usage

tableMeasurementValueAsConcept(
  result,
  header = c(visOmopResults::strataColumns(result)),
  groupColumn = c("codelist_name"),
  settingsColumn = character(),
  hide = character(),
  style = NULL,
  type = NULL,
  .options = list()
)

Arguments

result

A summarised_result object.

header

Columns to use as header. See options with `visOmopResults::tableColumns(result)`.

groupColumn

Columns to group by. See options with `visOmopResults::tableColumns(result)`.

settingsColumn

Columns from settings to include in results. See options with `visOmopResults::settingsColumns(result)`.

hide

Columns to hide from the visualisation. See options with `visOmopResults::tableColumns(result)`.

style

Named list that specifies how to style the different parts of the table generated. It can either be a pre-defined style ("default" or "darwin" - the latter just for gt and flextable), or NULL which converts to "default" style, or custom code.

type

Type of table. Check supported types with `visOmopResults::tableType()`. If NULL 'gt' type will be used.

.options

A named list with additional formatting options. `visOmopResults::tableOptions()` shows allowed arguments and their default values.

Value

A formatted table

Examples

# \donttest{
library(MeasurementDiagnostics)

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
#>  The following estimates will be computed:
#>  time: 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 2026-01-15 11:41:56.48987
#>  Summary finished, at 2026-01-15 11:41:56.599453
#> → Getting measurements per subject.
#> Summarising subjects
#>  The following estimates will be computed:
#>  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 2026-01-15 11:41:57.065609
#>  Summary finished, at 2026-01-15 11:41:57.168299
#> → Summarising results - value as number.
#> Summarising value as number
#>  The following estimates will be computed:
#>  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 2026-01-15 11:41:58.279941
#>  Summary finished, at 2026-01-15 11:41:58.55264
#> → Summarising results - value as concept.
#> Summarising value as number
#>  The following estimates will be computed:
#>  value_as_concept_id: count, percentage
#> → Start summary of data, at 2026-01-15 11:41:59.150314
#>  Summary finished, at 2026-01-15 11:41:59.304613
#> → Binding all diagnostic results.

tableMeasurementValueAsConcept(result)
CDM name Concept name Concept ID Source concept name Source concept ID Domain ID Value as concept name Value as concept ID Estimate name Estimate value
test_codelist
unknown overall overall overall overall overall Low 4267416 N (%) 68 (34.00%)
High 4328749 N (%) 66 (33.00%)
NA NA N (%) 66 (33.00%)
Alkaline phosphatase.bone [Enzymatic activity/volume] in Serum or Plasma 3001467 NA NA Measurement Low 4267416 N (%) 68 (34.00%)
High 4328749 N (%) 66 (33.00%)
NA NA N (%) 66 (33.00%)
CDMConnector::cdmDisconnect(cdm = cdm) # }