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Convert a gtstats result to a gt table

Source: R/to_gt.R
to_gt.Rd

Render supported gtstats objects as formatted gt tables.

Usage

to_gt(
  x,
  title = NULL,
  subtitle = NULL,
  bold_labels = TRUE,
  show_footnotes = TRUE
)

Arguments

x

A supported gtstats object.

title

Optional table title.

subtitle

Optional table subtitle.

bold_labels

Logical; whether to bold variable labels where appropriate.

show_footnotes

Logical; whether explanatory footnotes should be displayed.

Value

A gt_tbl object.

Details

This function is the explicit rendering bridge between analytical gtstats objects and presentation-ready table output. It supports descriptive, inferential, epidemiological, and table-builder objects created by the package and applies a consistent visual style using gt.

Supported inputs include:

  • gt_describe

  • gt_distribution

  • gt_variance

  • gt_compare

  • gt_correlation

  • gt_effect

  • gt_prop

  • gt_rate

  • gt_twobytwo

  • gtstats_summary

  • gt_data_table

Examples

to_gt(describe_data(mtcars))



  
Variable
      Type
      Complete
      Unique
      Overview
      Range / levels
    
mpg
continuous
32/32 (100.0%)
25
Mean 20.09 (SD 6.03); median 19.20
10.40 to 33.90
cyl
categorical
32/32 (100.0%)
3
8 14 (43.8%); 4 11 (34.4%); 6 7 (21.9%)
6, 4, 8
disp
continuous
32/32 (100.0%)
27
Mean 230.72 (SD 123.94); median 196.30
71.10 to 472.00
hp
continuous
32/32 (100.0%)
22
Mean 146.69 (SD 68.56); median 123.00
52.00 to 335.00
drat
continuous
32/32 (100.0%)
22
Mean 3.60 (SD 0.53); median 3.70
2.76 to 4.93
wt
continuous
32/32 (100.0%)
29
Mean 3.22 (SD 0.98); median 3.33
1.51 to 5.42
qsec
continuous
32/32 (100.0%)
30
Mean 17.85 (SD 1.79); median 17.71
14.50 to 22.90
vs
binary
32/32 (100.0%)
2
0 18 (56.2%); 1 14 (43.8%)
0, 1
am
binary
32/32 (100.0%)
2
0 19 (59.4%); 1 13 (40.6%)
1, 0
gear
categorical*
32/32 (100.0%)
3
3 15 (46.9%); 4 12 (37.5%); 5 5 (15.6%)
4, 3, 5
carb
continuous
32/32 (100.0%)
6
Mean 2.81 (SD 1.62); median 2.00
1.00 to 8.00
* Possible ordinal or count-coded variable. Confirm the intended meaning and order using the data dictionary or clinical context.
    

to_gt(summary_table(mtcars, by = am, include = c(mpg, wt)))



  
Characteristic1
      1

N = 131		
      0

N = 191		
    
mpg
24.4 (6.2)
17.1 (3.8)
wt
2.4 (0.6)
3.8 (0.8)
1 Continuous data are mean (SD).
    

to_gt(compare_groups(mtcars, variable = mpg, group = am))



  
Variable
      0

N = 19		
      1

N = 13		
      Mean difference (95% CI)1
      p-value2
    
mpg
17.15 (3.83)
24.39 (6.17)
-7.24 (-11.28 to -3.21)
<0.01
1 Difference is 0 minus 1.
    
2 Welch t-test
    

to_gt(
  summary_table(
    mtcars,
    by = am,
    include = c(mpg, wt, cyl),
    overall = TRUE
  ) |>
    add_total() |>
    add_p()
)



  
Characteristic1
      Overall

N = 321		
      1

N = 131		
      0

N = 191		
      p-value2
    
mpg
20.1 (6.0)
24.4 (6.2)
17.1 (3.8)
0.001ᵃ
wt
3.2 (1.0)
2.4 (0.6)
3.8 (0.8)
<0.001ᵃ
cyl



0.007ᵇ
4
11 (34.4%)
8 (61.5%)
3 (15.8%)

6
7 (21.9%)
3 (23.1%)
4 (21.1%)

8
14 (43.8%)
2 (15.4%)
12 (63.2%)

Total (N)
32
13
19

1 Continuous data are mean (SD). Categorical data are n (%).
    
2 ᵃ Welch t-test; ᵇ Fisher's exact test (Monte Carlo p-value)