Generate a formatted table from a <data.table>

This function combines the functionalities of formatEstimateValue(), formatEstimateName(), formatHeader(), and formatTable() into a single function. While it does not require the input table to be a <summarised_result>, it does expect specific fields to apply some formatting functionalities.

Usage

visTable(
  result,
  estimateName = character(),
  header = character(),
  groupColumn = character(),
  rename = character(),
  type = "gt",
  hide = character(),
  .options = list()
)

Arguments

result

A table to format.

estimateName

A named list of estimate names to join, sorted by computation order. Use <...> to indicate estimate names. This argument requires that the table has estimate_name and estimate_value columns.

header

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The vector elements can be column names or labels for overall headers. The table must contain an estimate_value column to pivot the headers.

groupColumn

Columns to use as group labels. 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 them to sentence case. Use rename to customize specific column names.

rename

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

type

The desired format of the output table. See tableType() for allowed options.

hide

Columns to drop from the output table.

.options

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

Value

A tibble, gt, or flextable object.

Examples

result <- mockSummarisedResult()
result |>
  visTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("Estimate"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = c("strata_name", "strata_level"),
    hide = c("additional_name", "additional_level", "estimate_type", "result_type")
  )


  
Result id
      
Database name
      
Group name
      
Group level
      
Variable name
      
Variable level
      
Estimate name
      
Estimate
    
overall; overall
    
1
mock
cohort_name
cohort1
number subjects
-
N
7,299,699



cohort2
number subjects
-
N
9,711,406



cohort1
age
-
Mean (SD)
43.56 (1.11)



cohort2
age
-
Mean (SD)
96.10 (1.61)



cohort1
Medications
Amoxiciline
N%
99,345 (40.69)



cohort2
Medications
Amoxiciline
N%
85,121 (49.19)



cohort1
Medications
Ibuprofen
N%
15,376 (2.15)



cohort2
Medications
Ibuprofen
N%
2,507 (65.38)
age_group &&& sex; <40 &&& Male
    
1
mock
cohort_name
cohort1
number subjects
-
N
8,941,871



cohort2
number subjects
-
N
2,327,210



cohort1
age
-
Mean (SD)
28.93 (9.38)



cohort2
age
-
Mean (SD)
27.06 (1.76)



cohort1
Medications
Amoxiciline
N%
62,749 (1.94)



cohort2
Medications
Amoxiciline
N%
48,000 (44.66)



cohort1
Medications
Ibuprofen
N%
94,473 (25.28)



cohort2
Medications
Ibuprofen
N%
75,234 (35.33)
age_group &&& sex; >=40 &&& Male
    
1
mock
cohort_name
cohort1
number subjects
-
N
2,203,064



cohort2
number subjects
-
N
8,674,180



cohort1
age
-
Mean (SD)
63.76 (8.46)



cohort2
age
-
Mean (SD)
73.06 (1.98)



cohort1
Medications
Amoxiciline
N%
1,463 (5.02)



cohort2
Medications
Amoxiciline
N%
53,727 (69.02)



cohort1
Medications
Ibuprofen
N%
51,947 (65.67)



cohort2
Medications
Ibuprofen
N%
73,207 (59.66)
age_group &&& sex; <40 &&& Female
    
1
mock
cohort_name
cohort1
number subjects
-
N
2,915,964



cohort2
number subjects
-
N
1,107,617



cohort1
age
-
Mean (SD)
26.45 (5.71)



cohort2
age
-
Mean (SD)
13.42 (3.58)



cohort1
Medications
Amoxiciline
N%
20,518 (70.23)



cohort2
Medications
Amoxiciline
N%
66,164 (84.27)



cohort1
Medications
Ibuprofen
N%
45,563 (78.91)



cohort2
Medications
Ibuprofen
N%
40,911 (72.77)
age_group &&& sex; >=40 &&& Female
    
1
mock
cohort_name
cohort1
number subjects
-
N
8,128,987



cohort2
number subjects
-
N
8,014,918



cohort1
age
-
Mean (SD)
38.63 (6.79)



cohort2
age
-
Mean (SD)
4.84 (1.81)



cohort1
Medications
Amoxiciline
N%
66,308 (6.64)



cohort2
Medications
Amoxiciline
N%
30,085 (37.58)



cohort1
Medications
Ibuprofen
N%
22,009 (70.88)



cohort2
Medications
Ibuprofen
N%
63,086 (99.56)
sex; Male
    
1
mock
cohort_name
cohort1
number subjects
-
N
436,023



cohort2
number subjects
-
N
6,579,245



cohort1
age
-
Mean (SD)
61.92 (0.89)



cohort2
age
-
Mean (SD)
70.36 (5.61)



cohort1
Medications
Amoxiciline
N%
46,374 (3.61)



cohort2
Medications
Amoxiciline
N%
26,350 (98.49)



cohort1
Medications
Ibuprofen
N%
13,918 (6.46)



cohort2
Medications
Ibuprofen
N%
6,544 (49.81)
sex; Female
    
1
mock
cohort_name
cohort1
number subjects
-
N
5,052,717



cohort2
number subjects
-
N
6,520,543



cohort1
age
-
Mean (SD)
54.17 (7.85)



cohort2
age
-
Mean (SD)
14.72 (6.59)



cohort1
Medications
Amoxiciline
N%
36,035 (2.02)



cohort2
Medications
Amoxiciline
N%
30,505 (95.24)



cohort1
Medications
Ibuprofen
N%
21,616 (51.13)



cohort2
Medications
Ibuprofen
N%
14,869 (23.03)
age_group; <40
    
1
mock
cohort_name
cohort1
number subjects
-
N
2,416,559



cohort2
number subjects
-
N
2,263,226



cohort1
age
-
Mean (SD)
48.48 (2.27)



cohort2
age
-
Mean (SD)
76.92 (6.60)



cohort1
Medications
Amoxiciline
N%
68,937 (37.28)



cohort2
Medications
Amoxiciline
N%
87,496 (98.99)



cohort1
Medications
Ibuprofen
N%
40,568 (20.09)



cohort2
Medications
Ibuprofen
N%
27,970 (30.13)
age_group; >=40
    
1
mock
cohort_name
cohort1
number subjects
-
N
5,891,424



cohort2
number subjects
-
N
8,539,796



cohort1
age
-
Mean (SD)
76.43 (4.48)



cohort2
age
-
Mean (SD)
17.64 (0.02)



cohort1
Medications
Amoxiciline
N%
25,886 (22.57)



cohort2
Medications
Amoxiciline
N%
71,844 (44.31)



cohort1
Medications
Ibuprofen
N%
23,373 (81.41)



cohort2
Medications
Ibuprofen
N%
85,066 (72.05)