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Create a baseline table

Source: R/baseline_table.R
create_baseline.Rd

Create a baseline table

Usage

create_baseline(
  data,
  ...,
  by.var,
  add.p = FALSE,
  add.overall = FALSE,
  theme = c("jama", "lancet", "nejm", "qjecon"),
  detail_level = c("minimal", "extended")
)

Arguments

data

data

...

passed as fun.arg to baseline_table()

by.var

specify stratification variable

add.p

add comparison/p-value

add.overall

add overall column

theme

set table theme

detail_level

specify detail level. Either "minimal" or "extended".

Value

gtsummary table list object

Examples

mtcars |> create_baseline(by.var = "gear", add.p = "yes" == "yes")



  
Characteristic
      3

N = 15		
      4

N = 12		
      5

N = 5		
      p-value1
    
mpg, Median (IQR)
15.5 (14.3 – 18.7)
22.8 (21.0 – 28.9)
19.7 (15.8 – 26.0)
<0.001
cyl, n (%)






<0.001
    4
1 (6.7)
8 (67)
2 (40)

    6
2 (13)
4 (33)
1 (20)

    8
12 (80)
0 (0)
2 (40)

disp, Median (IQR)
318 (276 – 400)
131 (79 – 160)
145 (120 – 301)
<0.001
hp, Median (IQR)
180 (150 – 215)
94 (66 – 110)
175 (113 – 264)
<0.001
drat, Median (IQR)
3.08 (3.00 – 3.21)
3.92 (3.90 – 4.10)
3.77 (3.62 – 4.22)
<0.001
wt, Median (IQR)
3.73 (3.44 – 4.07)
2.70 (2.07 – 3.17)
2.77 (2.14 – 3.17)
<0.001
qsec, Median (IQR)
17.42 (17.02 – 18.00)
18.76 (18.41 – 19.69)
15.50 (14.60 – 16.70)
0.002
vs, n (%)
3 (20)
10 (83)
1 (20)
0.001
am, n (%)
0 (0)
8 (67)
5 (100)
<0.001
carb, n (%)






0.24
    1
3 (20)
4 (33)
0 (0)

    2
4 (27)
4 (33)
2 (40)

    3
3 (20)
0 (0)
0 (0)

    4
5 (33)
4 (33)
1 (20)

    6
0 (0)
0 (0)
1 (20)

    8
0 (0)
0 (0)
1 (20)

1 Kruskal-Wallis rank sum test; Fisher’s exact test
    
mtcars |> create_baseline(by.var = "gear", detail_level = "extended")



  
Characteristic
      3

N = 15		
      4

N = 12		
      5

N = 5		
    
mpg





    Median (Q1, Q3)
15.5 (14.3, 18.7)
22.8 (21.0, 28.9)
19.7 (15.8, 26.0)
    Mean (SD)
16.1 (3.4)
24.5 (5.3)
21.4 (6.7)
    Min, Max
10.4, 21.5
17.8, 33.9
15.0, 30.4
cyl, n (%)





    4
1 (6.7)
8 (67)
2 (40)
    6
2 (13)
4 (33)
1 (20)
    8
12 (80)
0 (0)
2 (40)
disp





    Median (Q1, Q3)
318 (276, 400)
131 (79, 160)
145 (120, 301)
    Mean (SD)
326 (95)
123 (39)
202 (115)
    Min, Max
120, 472
71, 168
95, 351
hp





    Median (Q1, Q3)
180 (150, 215)
94 (66, 110)
175 (113, 264)
    Mean (SD)
176 (48)
90 (26)
196 (103)
    Min, Max
97, 245
52, 123
91, 335
drat





    Median (Q1, Q3)
3.08 (3.00, 3.21)
3.92 (3.90, 4.10)
3.77 (3.62, 4.22)
    Mean (SD)
3.13 (0.27)
4.04 (0.31)
3.92 (0.39)
    Min, Max
2.76, 3.73
3.69, 4.93
3.54, 4.43
wt





    Median (Q1, Q3)
3.73 (3.44, 4.07)
2.70 (2.07, 3.17)
2.77 (2.14, 3.17)
    Mean (SD)
3.89 (0.83)
2.62 (0.63)
2.63 (0.82)
    Min, Max
2.47, 5.42
1.62, 3.44
1.51, 3.57
qsec





    Median (Q1, Q3)
17.42 (17.02, 18.00)
18.76 (18.41, 19.69)
15.50 (14.60, 16.70)
    Mean (SD)
17.69 (1.35)
18.97 (1.61)
15.64 (1.13)
    Min, Max
15.41, 20.22
16.46, 22.90
14.50, 16.90
vs, n (%)





    0
12 (80)
2 (17)
4 (80)
    1
3 (20)
10 (83)
1 (20)
am, n (%)





    0
15 (100)
4 (33)
0 (0)
    1
0 (0)
8 (67)
5 (100)
carb, n (%)





    1
3 (20)
4 (33)
0 (0)
    2
4 (27)
4 (33)
2 (40)
    3
3 (20)
0 (0)
0 (0)
    4
5 (33)
4 (33)
1 (20)
    6
0 (0)
0 (0)
1 (20)
    8
0 (0)
0 (0)
1 (20)
mtcars |> create_baseline(by.var = "gear", detail_level = "extended",type = list(gtsummary::all_dichotomous() ~ "categorical"),theme="nejm")



  
Characteristic
      3

N = 151		
      4

N = 121		
      5

N = 51		
    
mpg
15.5 (14.3 – 18.7)
22.8 (21.0 – 28.9)
19.7 (15.8 – 26.0)
cyl





    4
1 (6.7)
8 (67)
2 (40)
    6
2 (13)
4 (33)
1 (20)
    8
12 (80)
0 (0)
2 (40)
disp
318 (276 – 400)
131 (79 – 160)
145 (120 – 301)
hp
180 (150 – 215)
94 (66 – 110)
175 (113 – 264)
drat
3.08 (3.00 – 3.21)
3.92 (3.90 – 4.10)
3.77 (3.62 – 4.22)
wt
3.73 (3.44 – 4.07)
2.70 (2.07 – 3.17)
2.77 (2.14 – 3.17)
qsec
17.42 (17.02 – 18.00)
18.76 (18.41 – 19.69)
15.50 (14.60 – 16.70)
vs





    0
12 (80)
2 (17)
4 (80)
    1
3 (20)
10 (83)
1 (20)
am





    0
15 (100)
4 (33)
0 (0)
    1
0 (0)
8 (67)
5 (100)
carb





    1
3 (20)
4 (33)
0 (0)
    2
4 (27)
4 (33)
2 (40)
    3
3 (20)
0 (0)
0 (0)
    4
5 (33)
4 (33)
1 (20)
    6
0 (0)
0 (0)
1 (20)
    8
0 (0)
0 (0)
1 (20)
1 Median (IQR); n (%)
    

create_baseline(default_parsing(mtcars), by.var = "am", add.p = FALSE, add.overall = FALSE, theme = "lancet")



  
Characteristic
      FALSE

N = 191		
      TRUE

N = 131		
    
mpg
17·3 (14·7 – 19·2)
22·8 (21·0 – 30·4)
cyl



    4
3 (16%)
8 (62%)
    6
4 (21%)
3 (23%)
    8
12 (63%)
2 (15%)
disp
276 (168 – 360)
120 (79 – 160)
hp
175 (110 – 205)
109 (66 – 113)
drat
3·15 (3·07 – 3·70)
4·08 (3·85 – 4·22)
wt
3·52 (3·44 – 3·85)
2·32 (1·94 – 2·78)
qsec
17·82 (17·05 – 19·44)
17·02 (16·46 – 18·61)
vs
7 (37%)
7 (54%)
gear



    3
15 (79%)
0 (0%)
    4
4 (21%)
8 (62%)
    5
0 (0%)
5 (38%)
carb



    1
3 (16%)
4 (31%)
    2
6 (32%)
4 (31%)
    3
3 (16%)
0 (0%)
    4
7 (37%)
3 (23%)
    6
0 (0%)
1 (7·7%)
    8
0 (0%)
1 (7·7%)
1 Median (IQR); n (%)