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Table 1 NoteBook
ATTENTION : pour faciliter la lecture de ce tutoriel, nous allons assumer que les conditions de validité des principaux tests (Chi2 et Student) sont respectés. Il vous faudra bien entendu les vérifier de votre côté.
Nous allons commencer par récupérer un dataframe sur Kaggle concernant le risque cardiovasculaire :
https://www.kaggle.com/yassinehamdaoui1/cardiovascular-disease/download/ds3WrBuyDewR9rMbNdTR%2Fversions%2FNWMwUpq65Kh9rqczUgk0%2Ffiles%2Fcardiovascular.txt
On va également installer les différents packages dont on aura besoin à savoir - tableOne - officer - flextable - magrittr
On ouvre le dataframe
setwd("~/destination")
Database <- read.table("cardiovascular.txt", header = TRUE, sep = ";")
str(Database)## 'data.frame': 462 obs. of 11 variables:
## $ ind : int 1 2 3 4 5 6 7 8 9 10 ...
## $ sbp : int 160 144 118 170 134 132 142 114 114 132 ...
## $ tobacco : num 12 0.01 0.08 7.5 13.6 6.2 4.05 4.08 0 0 ...
## $ ldl : num 5.73 4.41 3.48 6.41 3.5 6.47 3.38 4.59 3.83 5.8 ...
## $ adiposity: num 23.1 28.6 32.3 38 27.8 ...
## $ famhist : Factor w/ 2 levels "Absent","Present": 2 1 2 2 2 2 1 2 2 2 ...
## $ typea : int 49 55 52 51 60 62 59 62 49 69 ...
## $ obesity : num 25.3 28.9 29.1 32 26 ...
## $ alcohol : num 97.2 2.06 3.81 24.26 57.34 ...
## $ age : int 52 63 46 58 49 45 38 58 29 53 ...
## $ chd : int 1 1 0 1 1 0 0 1 0 1 ...Database = Database[,-1]
str(Database)## 'data.frame': 462 obs. of 10 variables:
## $ sbp : int 160 144 118 170 134 132 142 114 114 132 ...
## $ tobacco : num 12 0.01 0.08 7.5 13.6 6.2 4.05 4.08 0 0 ...
## $ ldl : num 5.73 4.41 3.48 6.41 3.5 6.47 3.38 4.59 3.83 5.8 ...
## $ adiposity: num 23.1 28.6 32.3 38 27.8 ...
## $ famhist : Factor w/ 2 levels "Absent","Present": 2 1 2 2 2 2 1 2 2 2 ...
## $ typea : int 49 55 52 51 60 62 59 62 49 69 ...
## $ obesity : num 25.3 28.9 29.1 32 26 ...
## $ alcohol : num 97.2 2.06 3.81 24.26 57.34 ...
## $ age : int 52 63 46 58 49 45 38 58 29 53 ...
## $ chd : int 1 1 0 1 1 0 0 1 0 1 ...Database$tobacco = ifelse(Database$tobacco=="0","0","1")
Database$obesity = ifelse(Database$obesity<30,"0","1")
str(Database)## 'data.frame': 462 obs. of 10 variables:
## $ sbp : int 160 144 118 170 134 132 142 114 114 132 ...
## $ tobacco : chr "1" "1" "1" "1" ...
## $ ldl : num 5.73 4.41 3.48 6.41 3.5 6.47 3.38 4.59 3.83 5.8 ...
## $ adiposity: num 23.1 28.6 32.3 38 27.8 ...
## $ famhist : Factor w/ 2 levels "Absent","Present": 2 1 2 2 2 2 1 2 2 2 ...
## $ typea : int 49 55 52 51 60 62 59 62 49 69 ...
## $ obesity : chr "0" "0" "0" "1" ...
## $ alcohol : num 97.2 2.06 3.81 24.26 57.34 ...
## $ age : int 52 63 46 58 49 45 38 58 29 53 ...
## $ chd : int 1 1 0 1 1 0 0 1 0 1 ...varsToFactor <- c("tobacco", "obesity", "chd")
Database[varsToFactor] <- lapply(Database[varsToFactor], factor)
str(Database)## 'data.frame': 462 obs. of 10 variables:
## $ sbp : int 160 144 118 170 134 132 142 114 114 132 ...
## $ tobacco : Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 1 1 ...
## $ ldl : num 5.73 4.41 3.48 6.41 3.5 6.47 3.38 4.59 3.83 5.8 ...
## $ adiposity: num 23.1 28.6 32.3 38 27.8 ...
## $ famhist : Factor w/ 2 levels "Absent","Present": 2 1 2 2 2 2 1 2 2 2 ...
## $ typea : int 49 55 52 51 60 62 59 62 49 69 ...
## $ obesity : Factor w/ 2 levels "0","1": 1 1 1 2 1 2 1 1 1 2 ...
## $ alcohol : num 97.2 2.06 3.81 24.26 57.34 ...
## $ age : int 52 63 46 58 49 45 38 58 29 53 ...
## $ chd : Factor w/ 2 levels "0","1": 2 2 1 2 2 1 1 2 1 2 ...La variable qui nous intéresse ici est “chd” à savoir maladie cardiovasculaire. On va créer une table 1 en s’intéressant à 2 groupes : antécédent familial oui/non
On va en profiter pour récupérer le nom de toutes nos variables
dput(names(Database))## c("sbp", "tobacco", "ldl", "adiposity", "famhist", "typea", "obesity",
## "alcohol", "age", "chd")MyVars = c("sbp", "tobacco", "ldl", "adiposity", "typea", "obesity",
"alcohol", "age", "chd")- On créé la table 1 globale
library(tableone)
tab1a <- CreateTableOne(vars = MyVars, data = Database)
tab1a <- print(tab1a, quote = FALSE, noSpaces = TRUE, printToggle = FALSE, showAllLevels = TRUE)
tab1a##
## level Overall
## n "" "462"
## sbp (mean (SD)) "" "138.33 (20.50)"
## tobacco (%) "0" "107 (23.2)"
## "1" "355 (76.8)"
## ldl (mean (SD)) "" "4.74 (2.07)"
## adiposity (mean (SD)) "" "25.41 (7.78)"
## typea (mean (SD)) "" "53.10 (9.82)"
## obesity (%) "0" "389 (84.2)"
## "1" "73 (15.8)"
## alcohol (mean (SD)) "" "17.04 (24.48)"
## age (mean (SD)) "" "42.82 (14.61)"
## chd (%) "0" "302 (65.4)"
## "1" "160 (34.6)"- On créée la table 1 par groupe
tab1b <- CreateTableOne(vars = MyVars, strata = "famhist", data = Database)
tab1b <- print(tab1b, quote = FALSE, noSpaces = TRUE, printToggle = FALSE, showAllLevels = TRUE)
tab1b## Stratified by famhist
## level Absent Present p test
## n "" "270" "192" "" ""
## sbp (mean (SD)) "" "136.85 (20.58)" "140.41 (20.25)" "0.066" ""
## tobacco (%) "0" "74 (27.4)" "33 (17.2)" "0.014" ""
## "1" "196 (72.6)" "159 (82.8)" "" ""
## ldl (mean (SD)) "" "4.46 (2.03)" "5.14 (2.07)" "<0.001" ""
## adiposity (mean (SD)) "" "24.22 (7.89)" "27.08 (7.33)" "<0.001" ""
## typea (mean (SD)) "" "52.73 (9.94)" "53.62 (9.64)" "0.337" ""
## obesity (%) "0" "236 (87.4)" "153 (79.7)" "0.035" ""
## "1" "34 (12.6)" "39 (20.3)" "" ""
## alcohol (mean (SD)) "" "15.38 (21.62)" "19.38 (27.91)" "0.084" ""
## age (mean (SD)) "" "39.87 (15.30)" "46.96 (12.48)" "<0.001" ""
## chd (%) "0" "206 (76.3)" "96 (50.0)" "<0.001" ""
## "1" "64 (23.7)" "96 (50.0)" "" ""- On va maintenant sortir une belle table Word
tab1f = cbind(as.data.frame(tab1a), as.data.frame(tab1b))Je vous encourage à ouvrir le DataFrame avec la fonction :
View(tab1f)- On va retirer la colonne test qui ne sert à rien, et la seconde colonne level qui est redondante (on voit que ce sont les colonnes 3 et 7)
tab1f = tab1f[,-c(3,7)]tab1f <- cbind(Variable = rownames(tab1f), tab1f)library(officer)
library(flextable)
library(magrittr)
ft <- flextable(data = tab1f) %>%
autofit
tmp <- tempfile(fileext = ".docx")
read_docx() %>%
body_add_flextable(ft) %>%
print(target = tmp)
browseURL(tmp)
ft
Variable
|
level
|
Overall
|
Absent
|
Present
|
p
|
n
|
462
|
270
|
192
| ||
sbp..mean..SD..
|
138.33 (20.50)
|
136.85 (20.58)
|
140.41 (20.25)
|
0.066
| |
tobacco....
|
0
|
107 (23.2)
|
74 (27.4)
|
33 (17.2)
|
0.014
|
X
|
1
|
355 (76.8)
|
196 (72.6)
|
159 (82.8)
| |
ldl..mean..SD..
|
4.74 (2.07)
|
4.46 (2.03)
|
5.14 (2.07)
|
<0.001
| |
adiposity..mean..SD..
|
25.41 (7.78)
|
24.22 (7.89)
|
27.08 (7.33)
|
<0.001
| |
typea..mean..SD..
|
53.10 (9.82)
|
52.73 (9.94)
|
53.62 (9.64)
|
0.337
| |
obesity....
|
0
|
389 (84.2)
|
236 (87.4)
|
153 (79.7)
|
0.035
|
X.1
|
1
|
73 (15.8)
|
34 (12.6)
|
39 (20.3)
| |
alcohol..mean..SD..
|
17.04 (24.48)
|
15.38 (21.62)
|
19.38 (27.91)
|
0.084
| |
age..mean..SD..
|
42.82 (14.61)
|
39.87 (15.30)
|
46.96 (12.48)
|
<0.001
| |
chd....
|
0
|
302 (65.4)
|
206 (76.3)
|
96 (50.0)
|
<0.001
|
X.2
|
1
|
160 (34.6)
|
64 (23.7)
|
96 (50.0)
|
