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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
      Is required
      Estimate name
      
        
Data source

      		
    
GiBleed
    
all
Number records
–
overall
N
5,343

Number subjects
–
overall
N
5,343

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

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




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




Range [min to max]
[1 to 1]

Duration in days
–
overall
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
overall
N (%)
5,343 (100.00%)

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

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

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


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




N zeros (%)
0 (0.00%)


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


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




N zeros (%)
0 (0.00%)


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




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

Duration in days
–
overall
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)
# }