Generate a formatted table from a <summarised_result>

This function combines the functionalities of formatEstimateValue(), estimateName(), formatHeader(), and formatTable() into a single function specifically for <summarised_result> objects.

Usage

visOmopTable(
  result,
  estimateName = character(),
  header = character(),
  settingsColumn = character(),
  groupColumn = character(),
  rename = character(),
  type = NULL,
  hide = character(),
  columnOrder = character(),
  factor = list(),
  style = NULL,
  showMinCellCount = TRUE,
  .options = list()
)

Arguments

result

A <summarised_result> object.

estimateName

A named list of estimate names to join, sorted by computation order. Use <...> to indicate estimate names.

header

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

• Any of the columns returned by tableColumns(result) to create a header for these columns.

• Any other input to create an overall header.

settingsColumn

A character vector with the names of settings to include in the table. To see options use settingsColumns(result).

groupColumn

Columns to use as group labels, to see options use tableColumns(result). By default, the name of the new group will be the tidy* column names separated by ";". To specify a custom group name, use a named list such as: list("newGroupName" = c("variable_name", "variable_level")).

*tidy: The tidy format applied to column names replaces "_" with a space and converts to sentence case. Use rename to customise specific column names.

rename

A named vector to customise column names, e.g., c("Database name" = "cdm_name"). The function renames all column names not specified here into a tidy* format.

type

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

hide

Columns to drop from the output table. By default, result_id and estimate_type are always dropped.

columnOrder

Character vector establishing the position of the columns in the formatted table. Columns in either header, groupColumn, or hide will be ignored.

factor

A named list where names refer to columns (see available columns in tableColumns()) and list elements are the level order of that column to arrange the results. The column order in the list will be used for arranging the result.

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 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 (see setGlobalTableOptions()) or an existing _brand.yml file (if found); otherwise, the default style is applied. For more details, see the Styles vignette on the package website.

showMinCellCount

If TRUE, suppressed estimates will be indicated with "<{min_cell_count}", otherwise, the default na defined in .options will be used.

.options

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

Value

A formatted table of the class selected in "type" argument.

Examples

result <- mockSummarisedResult()
result |>
  visOmopTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result)
  )


  
Database name
      
Variable name
      
Variable level
      
Estimate name
      

        
Cohort name
      
    
cohort1
      
cohort2
    
overall; overall
    
mock
number subjects
–
N
2,655,087
617,863

age
–
Mean (SD)
38.00 (7.94)
38.24 (7.89)

Medications
Amoxiciline
N%
7,068 (34.67)
33,239 (71.25)


Ibuprofen
N%
23,963 (92.41)
60,493 (10.32)
<40; Male
    
mock
number subjects
–
N
3,721,239
2,059,746

age
–
Mean (SD)
77.74 (1.08)
86.97 (0.23)

Medications
Amoxiciline
N%
9,947 (33.38)
65,087 (40.00)


Ibuprofen
N%
5,893 (59.88)
65,472 (44.63)
>=40; Male
    
mock
number subjects
–
N
5,728,534
1,765,568

age
–
Mean (SD)
93.47 (7.24)
34.03 (4.77)

Medications
Amoxiciline
N%
31,627 (47.64)
25,802 (32.54)


Ibuprofen
N%
64,229 (97.62)
35,320 (64.01)
<40; Female
    
mock
number subjects
–
N
9,082,078
6,870,228

age
–
Mean (SD)
21.21 (4.11)
48.21 (7.32)

Medications
Amoxiciline
N%
51,863 (89.22)
47,855 (75.71)


Ibuprofen
N%
87,627 (73.18)
27,026 (99.18)
>=40; Female
    
mock
number subjects
–
N
2,016,819
3,841,037

age
–
Mean (SD)
65.17 (8.21)
59.96 (6.93)

Medications
Amoxiciline
N%
66,201 (86.43)
76,631 (20.27)


Ibuprofen
N%
77,891 (35.67)
99,268 (49.56)
overall; Male
    
mock
number subjects
–
N
8,983,897
7,698,414

age
–
Mean (SD)
12.56 (6.47)
49.35 (4.78)

Medications
Amoxiciline
N%
40,683 (39.00)
8,425 (71.11)


Ibuprofen
N%
79,731 (43.15)
63,349 (48.43)
overall; Female
    
mock
number subjects
–
N
9,446,753
4,976,992

age
–
Mean (SD)
26.72 (7.83)
18.62 (8.61)

Medications
Amoxiciline
N%
91,288 (77.73)
87,532 (12.17)


Ibuprofen
N%
45,527 (14.82)
21,321 (17.34)
<40; overall
    
mock
number subjects
–
N
6,607,978
7,176,185

age
–
Mean (SD)
38.61 (5.53)
82.74 (4.38)

Medications
Amoxiciline
N%
29,360 (96.06)
33,907 (24.55)


Ibuprofen
N%
41,008 (1.31)
12,937 (75.48)
>=40; overall
    
mock
number subjects
–
N
6,291,140
9,919,061

age
–
Mean (SD)
1.34 (5.30)
66.85 (2.45)

Medications
Amoxiciline
N%
45,907 (43.47)
83,944 (14.33)


Ibuprofen
N%
81,087 (71.56)
47,812 (45.39)
result |>
  visOmopTable(
    estimateName = c(
      "N%" = "<count> (<percentage>)",
      "N" = "<count>",
      "Mean (SD)" = "<mean> (<sd>)"
    ),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result),
    type = "reactable"
  )