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Create a visual table from a summariseObservationPeriod() result

Source: R/tableObservationPeriod.R
tableObservationPeriod.Rd

Create a visual table from a summariseObservationPeriod() result

Usage

tableObservationPeriod(
  result,
  header = "cdm_name",
  hide = omopgenerics::settingsColumns(result),
  groupColumn = omopgenerics::strataColumns(result),
  type = NULL,
  style = NULL
)

Arguments

result

A summarised_result object (output of summariseObservationPeriod()).

header

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header.

hide

Columns to drop from the output table.

groupColumn

Columns to use as group labels, to see options use visOmopResults::tableColumns(result).

type

Character string specifying the desired output table format. See visOmopResults::tableType() for supported table types. If type = NULL, global options (set via visOmopResults::setGlobalTableOptions()) will be used if available; otherwise, a default 'gt' table is created.

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

  1. Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See visOmopResults::tableStyle() for available options.

  2. YAML file path: Provide the path to an existing .yml file defining a new style.

  3. List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type.

If style = NULL, the function will use global options (seevisOmopResults::setGlobalTableOptions()) or a _brand.yml file (if found); otherwise, the default style is applied.

Value

A formatted table visualisation.

Examples

# \donttest{
library(OmopSketch)
library(dplyr, warn.conflicts = FALSE)
library(omock)

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

result <- summariseObservationPeriod(cdm = cdm)
#> Warning: ! There are 2649 individuals not included in the person table.

tableObservationPeriod(result = result)



  
Summary of observation_period table
  
Observation period ordinal
      Variable name
      Variable level
      Estimate name
      
        
CDM name

      		
    
GiBleed
    
all
Number records
–
N
5,343

Number subjects
–
N
5,343

Subjects not in person table
–
N (%)
2,649 (49.58%)

Records per person
–
Mean (SD)
1.00 (0.00)



Median [Q25 - Q75]
1 [1 - 1]



Range [min to max]
[1 to 1]

Duration in days
–
Mean (SD)
14,402.00 (8,725.34)



Median [Q25 - Q75]
13,868.00 [7,102.50 - 20,955.50]



Range [min to max]
[1.00 to 40,349.00]

Type concept id
Period covering healthcare encounters
N (%)
5,343 (100.00%)

Start date before birth date
–
N (%)
0 (0.00%)

End date before start date
–
N (%)
0 (0.00%)

Column name
Observation period end date
N missing data (%)
0 (0.00%)


Observation period id
N missing data (%)
0 (0.00%)



N zeros (%)
0 (0.00%)


Observation period start date
N missing data (%)
0 (0.00%)


Period type concept id
N missing data (%)
0 (0.00%)



N zeros (%)
0 (0.00%)


Person id
N missing data (%)
0 (0.00%)



N zeros (%)
0 (0.00%)
1st
Number subjects
–
N
5,343

Duration in days
–
Mean (SD)
14,402.00 (8,725.34)



Median [Q25 - Q75]
13,868.00 [7,102.50 - 20,955.50]



Range [min to max]
[1.00 to 40,349.00]

plotObservationPeriod(
  result = result,
  variableName = "Duration in days",
  plotType = "boxplot"
)


cdmDisconnect(cdm = cdm)
# }